Policy-based routing for mobile ad hoc networks running HTR protocol

Universidade Federal de Pernambuco

Centro de Informática

POLICY-BASED ROUTING FOR MOBILE

AD HOC NETWORKS RUNNING

HTR PROTOCOL

Gabriela Coutinho Machado de Souza

Recife

2013

Gabriela Coutinho Machado de Souza

POLICY-BASED ROUTING FOR MOBILE AD HOC NETWORKS

RUNNING HTR PROTOCOL: A CASE STUDY

Dissertation presented to the Computer

Science Post Graduation Program of the

Federal University of Pernambuco in partial

fullfilment of the requirements for the Degree

of Master in Computer Science.

Advisor: Judith Kelner

Recife

2013

Catalogação na fonte

Bibliotecária Joana D’Arc L. Salvador, CRB 4-572

Souza, Gabriela Coutinho Machado de.

Policy-based routing for mobile ad hoc networks

running HTR protocol / Gabriela Coutinho Machado

de Souza. – Recife: O Autor, 2013.

76 f.: fig., tab.

Orientador: Judith Kelner.

Dissertação (Mestrado) - Universidade Federal de

Pernambuco. CIN. Ciência da Computação, 2013.

Inclui referências.

1. Sistemas de comunicação sem fio. 2. Telefonia

celular. 3. Simulação (computadores). I.Kelner, Judith

(orientadora). II. Título.

Dissertação de Mestrado apresentada por Gabriela Coutinho Machado de Souza à Pós

Graduação em Ciência da Computação do Centro de Informática da Universidade Federal de

Pernambuco, sob o título “Policy-based Routing for Mobile ad hoc Networks Running the

HTR Protocol” orientada pela Profa. Judith Kelner e aprovada pela Banca Examinadora

formada pelos professores:

______________________________________________

Prof. Stênio Flávio de Lacerda Fernandes

Centro de Informática / UFPE

______________________________________________

Prof. Ramide Augusto Sales Dantas

Unidade Acadêmica de Informação e Comunicação / IFPB

_______________________________________________

Profa. Judith Kelner

Centro de Informática / UFPE

Visto e permitida a impressão.

Recife, 13 de setembro de 2013

___________________________________________________

Profa. Edna Natividade da Silva Barros

Coordenadora da Pós-Graduação em Ciência da Computação do Centro de Informática da Universidade Federal de Pernambuco.

RESUMO

O crescimento das vendas de aparelhos móveis em todo o mundo, bem como as previsões para os próximos anos são apontadas em diversos relatórios. No entanto, essa necessidade de colaboração ubíqua trouxe novas possibilidades e desafios para a comunidade científica. Redes móveis ad hoc (Mobile Ad hoc Networks - MANETs) surgem diante deste cenário e permite que dispositivos se comuniquem de forma autônoma, sem a necessidade de uma infraestrutura predefinida para fornecer comunicação e serviços. Porém, essa descentralização junto com as restrições naturais dos dispositivos móveis, proporcionar roteamento eficiente para MANETs permanece um desafio. Este trabalho propõe novas melhorias para o roteamento em MANETs que utilizam o protocolo HTR. Também considera o papel que usuários associados aos dispositivos desempenham dentro de uma organização. Desta forma, as políticas desenvolvidas podem guiar o roteamento também com base nestes papéis. Com este esquema, é possível melhorar a comunicação de acordo com necessidades de negócio e requerimentos de cenário. Para este fim, esta dissertação propõe um conjunto de políticas que afetam o comportamento do roteamento e analisa os impactos em termos de atraso, energia gasta e tempo de vida dos nós. Através de simulações, essas métricas são avaliadas também com variação de parâmetros como a quantidade de nós que participam da simulação, as características de mobilidade e o número de fontes de tráfego. Resultados mostram que é possível atingir esses objetivos sem causar grande impacto negativo no atraso fim a fim e no consumo de energia, duas métricas importantes em avaliações de redes MANET. Nós exploramos esses resultados em diversos cenários e detalhamos nossas descobertas, que podem servir como uma perspectiva diferente para futuras aplicações de redes MANET.

Palavras-chave: Comunicação móvel sem fio. “Mobile Ad hoc Networks” (MANET). Protocolo HTR. WiMAX. Wi-Fi. LTE. Simulation. “Policy Based Management” (PBM).

ABSTRACT

The increasing growth of mobile devices in the whole world, and the forecasts for the coming years has been indicated by several reports. Nonetheless, this need for ubiquitous collaboration has brought new possibilities and challenges to the scientific community. Mobile Ad hoc Networks (MANETs) emerges in this scenario allowing devices to interconnect autonomously, without the need of a fixed infrastructure, in order to provide communication and information services. Due to such decentralization and the natural constraints of mobile devices, it remains, to this day, a challenge to provide efficient routing for MANETs. In this dissertation we propose new routing enhancements based on policies for MANETs running the HTR protocol. We consider the role(s) a user associated to a device performs within an organization. Hence our policies can guide the routing based on these roles. With this scheme we improve communication according to different business needs and scenario requirements. To this end, we propose a set of policies that affects the routing behavior and present four case studies to present each policy. Then we analyze two policies in terms of end-to-end delay, and nodes’ lifetime. Through simulation we evaluate these metrics while varying parameters such as the amount of nodes participating in the network, the mobility characteristics, and the number of traffic sources. Our results show that it is possible to achieve these goals without causing great impact on the average end-to-end delay and energy consumption, two important metrics in any MANET evaluation. We explore the results in several scenarios and detail our findings, which can provide a different perspective for future MANET applications.

Keywords: Wireless Mobile Communication. Mobile Ad hoc Networks (MANET). HTR Protocol. WiMAX. Wi-Fi. LTE. Simulation. Policy Based Management.

LIST OF TABLES

TABLE 1:HTRTERMINOLOGY ... 17

TABLE 2:HTRFEATURES ... 18

TABLE 3:SIMULATION PARAMETERS ... 51

TABLE 4:ERROR MARGIN PER METRIC ... 53

TABLE 5:KE-G16 NODES SCENARIOS PARAMETERS ... 56

TABLE 6:SOURCES AVERAGE END-TO-END DELAY FOR STATIC 16 NODES SCENARIOS ... 58

TABLE 7:SOURCES AVERAGE END-TO-END DELAY FOR 16 NODES MOBILITY SCENARIOS ... 59

TABLE 8:36 NODES SCENARIOS PARAMETERS ... 60

TABLE 9:SOURCES AVERAGE END-TO-END DELAY ON 36 NODES STATIC SCENARIOS ... 61

TABLE 10:SOURCES AVERAGE END-TO-END DELAY ON 36 NODES MOBILITY SCENARIOS ... 62

TABLE 11:KE-G16 NODES SCENARIOS PARAMETERS ... 63

TABLE 12:SOURCES AVERAGE END-TO-END DELAY IN 16 NODES STATIC SCENARIOS ... 65

TABLE 13:SOURCES AVERAGE END-TO-END DELAY IN 16 NODES MOBILITY SCENARIO ... 66

TABLE 14:36 NODES SCENARIOS PARAMETERS ... 66

TABLE 15:SOURCES AVERAGE END-TO-END DELAY IN 36 NODES STATIC SCENARIO... 67

LIST OF FIGURES

FIGURE 1:HTR TERMINOLOGY (SOURCE [17]) ... 18

FIGURE 2:ORIGINAL PACKET FORMAT ... 19

FIGURE 3:ORIGINAL HELLO MESSAGE ... 19

FIGURE 4:ORIGINAL TC MESSAGE ... 20

FIGURE 5:SCENARIO ... 33

FIGURE 6:INFORMATION FLOW ... 33

FIGURE 7:MODIFIED HTRPACKET FORMAT ... 34

FIGURE 8:MODIFIED HELLOMESSAGE ... 35

FIGURE 9:MODIFIED TCMESSAGE ... 35

FIGURE 10:DOCTOR NODES ... 39

FIGURE 11:POSSIBLE PATHS WITH AND WITHOUT KE-G ACTIVATED ... 39

FIGURE 12:LTENODES ... 41

FIGURE 13:COMMUNICATION EXAMPLE ... 42

FIGURE 14:KE-I FUNCTIONING EXAMPLE ... 42

FIGURE 15:NETWORK EXAMPLE ... 44

FIGURE 16:POSSIBLE SGP PATHS ... 45

FIGURE 17:LBEXAMPLE ... 47

FIGURE 18:POSSIBLE PATHS FOR LB ... 47

FIGURE 19:DOCTORS' SURVIVABILITY TIME WITH POLICY ACTIVATION ON STATIC SCENARIOS WITH 16 NODES ... 57

FIGURE 20:COMMONS ENERGY ON 16 NODES STATIC SCENARIO WITH POLICY ACTIVATION ... 57

FIGURE 21:DOCTORS' LIFETIME IN 16 NODES MOBILITY SCENARIOS ... 59

FIGURE 22:DOCTORS LIFETIME IN 36 NODES STATIC SCENARIOS ... 60

FIGURE 23:COMMONS LIFETIME IN 36 NODES STATIC SCENARIOS ... 61

FIGURE 24:DOCTORS LIFETIME IN 36 NODES MOBILITY SCENARIOS ... 62

FIGURE 25:NURSES LIFETIME IN 16 NODES STATIC SCENARIOS ... 64

FIGURE 26:COMMONS ENERGY IN 16 NODES STATIC SCENARIO ... 65

FIGURE 27:NURSES LIFETIME ON 16 NODES MOBILITY SCENARIOS... 66

FIGURE 28:NURSES LIFETIME ON 36 NODES STATIC SCENARIOS ... 67

CONTENTS

CHAPTER 1 INTRODUCTION ... 9

1.1 MOTIVATION ... 9

1.2 OBJECTIVES AND RELEVANCY ... 11

1.3 BRIEF SOLUTION INTRODUCTION ... 12

1.4 DISSERTATION OUTLINE ... 12

CHAPTER 2 STATE OF THE ART ... 14

2.1 CONTEXTUALIZATION ... 14

2.1.1 INTRODUCTION ... 14

2.1.2 ROUTING PROTOCOLS ... 14

2.1.3 POLICY-BASED CONTEXT-AWARE COMMUNICATION ... 21

2.2 RELATED WORK ... 23

2.2.1 POLICY MANAGEMENT FRAMEWORKS ... 23

2.2.2 ENERGY REDUCTION TECHNIQUES ... 27

2.2.3 LOAD BALANCE TECHNIQUES ... 29

2.3 CHAPTER SUMMARY ... 31

CHAPTER 3 SOLUTION ... 32

3.1 SCENARIO ... 32

3.2 CHANGES IN THE HTR MESSAGES ... 34

3.2.1 HTRPACKET FORMAT ... 34

3.2.2 HELLO MESSAGES ... 34

3.2.3 TOPOLOGY CONTROL MESSAGES ... 35

3.3 HTRSCORE INCREMENT ... 36

3.4 POLICIES ... 36

3.4.1 THE “KEEP ENERGY”POLICIES ... 36

3.4.2 CLOSED-GROUP PRIORITIZATION ... 43

3.4.3 LOAD BALANCING POLICY ... 45

3.4.4 GROUP-BASED AUTHORIZATION AND OBLIGATION POLICIES ... 47

CHAPTER 4 EVALUATION METHODOLOGY ... 50

4.1 COMMUNICATION TECHNOLOGIES ... 50

4.2 IMPLEMENTATION SCENARIO ... 50

4.2.1 SIMULATION PARAMETERS ... 51

4.3 METRICS ... 52

4.4 STATISTICS FOR EVALUATION ... 52

4.4.1 SAMPLES TESTS ... 53

CHAPTER 5 RESULTS ... 55

5.1 KEEP ENERGY -GROUP ... 55

5.1.1 16 NODES SCENARIOS ... 56 5.1.2 36 NODES SCENARIOS ... 59 5.2 LOAD BALANCE ... 62 5.2.1 16 NODES SCENARIOS ... 63 5.2.2 36 NODES SCENARIOS ... 66 5.3 DISCUSSION ... 68 CHAPTER 6 CONCLUSION ... 69 REFERENCES ... 71

CHAPTER 1 INTRODUCTION

1.1 M

The increasing growth of mobile devices sales, and the forecasts for the coming years have been indicated by several reports pointing to a even more mobile future [1] [2][3]. All of these devices brought new forms of wireless communications to attend the users’ demand for constant connection and access to services.

Wireless networks of many types (cellular, wireless local, wireless metropolitan, wireless personal) have been in use in the whole world for decades now [4]. All these types of wireless networks have mainly, at least, one thing in common: they all depend on a fixed, predefined infrastructure to enable connectivity and provide services to the network participants. In this scenario, ad hoc networks emerge and innovates this concept by decentralizing the network. Ad hoc networks are wireless networks that do not rely on a predefined or fixed infrastructure to exist. They emerge from the connection of devices that act autonomously providing communication and services among all connected nodes. In the literature, several papers states that ad hoc networks are the future in wireless communication evolution [5] [6] because it allows communication and information sharing even in scenarios where a fixed infrastructure is not available or not reliable. This possibility makes ad hoc networks attractive to several scenarios, such as emergency situations [4], vehicular networks, and others.

A multi-hop ad hoc network that is composed of mobile devices is called Mobile Ad Hoc Network (MANET) [7]. Designed based on wireless networks, MANETs come with some of the traditional wireless network problems, such as bandwidth restriction problems and transmission quality. And new problems arise, such as the lack of infrastructure itself and the decentralization, alongside with the possibility of high mobility and heterogeneity of its users’ devices. With those problems, new challenges arise, such as: the need for a new routing protocol capable of supporting topology discovery and maintenance, as well as a effective interface addressing technique and efficient communication schemes to deal with the constant and unpredictable changes caused by such a dynamic topology and link instability.

Wireless communication has brought with it the possibility of connection between mobile devices, which popularity keeps on increasing to this day [8]. Wireless networks allow seamless communication between distant and heterogeneous nodes. Heterogeneity can be in terms of different vendors, difference in hardware characteristics. Also, heterogeneity can be in terms of multiple interfaces capable of accessing different medium technologies such as Bluetooth [9], Wireless Fidelity (Wi-Fi) [10], WiMAX [11] and LTE [11], on which we focus in

this dissertation. Node heterogeneity is another key factor that needs to be addressed for transparent communication in MANETs, because it opens new possibilities, and brings new challenges. For example, such heterogeneity allows the use of multiple technologies. The capability of choosing among the available technology for communication can depend, for instance, on the quality of the links available, at a certain moment, or on the energy that would be expended a determined interface.

Another challenge is that mobile devices have constrained capabilities, such as its limited processing and transmission power and its available batteries’ level. Energy is one of the greatest concerns when it comes to MANETs, because often MANET devices rely on batteries to stay connected and those are usually very limited resources. Solutions to provide efficient energy consumption for MANETs keeps on emerging and, as they have such dynamic topologies, each work focuses on improving energy consumption in determined scenarios.

Although it brings new challenges, the independency of an infrastructure allowed by MANETs is, also, one of its great benefits. Decentralization allows collaboration on scenarios where communication would not be possible or reliable, and this offers a new level of flexibility to build networks’ collaboration. Because of such advantages, which allow group coordinated communication and collaboration, in the last years those statements about MANETs were proven to be factual and mobile ad hoc networks are widely used in scenarios of disaster relief, battlefield, and emergency, rescue, sensor networks, among many others [4] [12] [13] [14] [15].

With such dynamic scenarios and heterogeneous possibilities comes the need for efficient end-to-end communication. This can be achieved by incorporating intelligent routing capabilities to MANET devices that support the Internet Protocol (IP) [16] [17]. To properly provide communication for MANETs and allow easy deployment and management, several routing protocols were proposed [4] [18] [19], and those are usually grouped into three main types: reactive, which are protocols that choose the next hop to reach a destination by broadcasting route request messages to its neighbors only when needed, and wait for the route request reply to choose the best node to forward the message; proactive are protocols that share topology and node information through the dissemination of periodic messages and, with such information, it maintains a routing table; and hybrid protocols, which have characteristics of both reactive and proactive protocols, depending on the needs the creators are trying to address. Each of these proposed protocols focus on fulfilling different requirements for specific scenarios. The most important routing protocols for MANETs of each of these types, together with its most important features, are described on the next chapter.

This master science dissertation is based on the Heterogeneous protocol (HTR) [17] a proactive routing framework, focused on supporting technology heterogeneity in terms of communication. HTR uses a metric called HTRScore to decide the best links to forward packets in order to reach a destination. This metric is based on some factors such as the energy level of the nodes and the probability of losing a packet due to link quality. Its main goal is to extend node survivability through energy saving. The HTR protocol introduces self-configuration support through the autonomic bootstrap process which allows the configuration of network interfaces requiring minimum human intervention. The HTR was previously implemented on a real scenario to test the heterogeneity support of the following technologies: Bluetooth [9], Wireless Fidelity (Wi-Fi), WiMAX and LTE. This implementation and the results are presented in [20]. The next chapter details the HTR characteristics, features, configuration process and the multiple interfaces with different technologies support.

The HTR provides proactive, heterogeneous routing to MANETs in an efficient and energy-aware manner. But, some scenarios have special requirements regarding the network participants, for example, on emergency scenarios, where different groups of users interact. These different groups may have different needs according to the role users perform and this should be taken into account when managing a MANET routing.

1.2 O

To improve the performance of routing protocols, several schemes were proposed for both proactive and reactive protocols. These solutions seek to consider the energy level of nodes, congestion avoidance, reduce communication delay, and provide load balancing, among others. The objective of this dissertation is to allow those benefits through the use of policies in MANET’s running HTR. By using users’ roles information we aim at control the HTR behavior to achieve specific goals through the use of policies. These goals vary from business requirements to network scenario achievements, always focusing on minimum human intervention. We propose and implement for evaluation a set of new policies for MANETs of different types, with different goals, and present 4 case studies based on these policies.

We present detailed case studies of all 4 policies and implement 2 of them on the Network Simulator 3 (NS-3) [21], testing them in different scenarios. We evaluate how each one of these policies affect the network’s behavior and its metrics, especially in terms of impact on energy consumption and delay.

To be able to consider users’ roles in our scenarios, we change the HTR control messages to include this information. This change will allow actions to be taken not only

influenced by node location or device capability, but also by its associated role, which is very important on some scenarios. For this reason is also an objective to present a real-life based scenario to contextualize the policies. This is another major differential of this dissertation, since we test and evaluate the impact of those policies on the network and not only present possible scenarios.

Another objective of this dissertation is to achieve route adaptation without introducing more messages in the network, because that would increase the amount of overhead.

Although several papers propose different schemes to address some of the same problems that we address, to the best of our knowledge, no solution was proposed and tested using policies based on human roles before, nor have tested how these policies really affect the network behavior and its metrics, and this is the greatest contribution expected with this dissertation.

1.3 B

S

I

Two of the proposed policies are focused on the extension of node survivability time through energy preservation. This is achieved, in the first policy, by avoiding that specific nodes are used as a router, unless it is the only option, saving the energy that would be spent on transmission. In the second policy, energy preservation is achieved by turning of the LTE interface, and it is also based on groups defined by users’ roles. The third policy considers the prioritization of communication via nodes of same group. The idea is that by knowing the source of the information, data transmission will preferably happen through nodes of the same group as the group of the source. The fourth policy is to balance the load among nodes without increasing delay to unreasonable values and avoiding that central nodes die faster, saving their energy. This is done by defining a load threshold that when reached, the HTRScore of the node is increased, changing the next hop option to avoid nodes with high possibility for congestion.

1.4 D

This chapter presented the main concepts necessary to understand our proposal. We introduce MANETs, along with its routing protocols and the need for an adaptive behavior. Finally, we give a brief introduction of our solution with its main objectives and the contributions expected with the work.

The remainder of this dissertation is presented as follows. Chapter 2 gives the background information on the main topics that form the basis of this dissertation. It introduces MANETs with details, also the main routing protocols for MANETs and its types,

and finally the HTR protocol and its metric HTRScore. It also contextualizes the work by presenting a review of the most important works related to the area of policy-based management for MANETs and show other solutions developed to address the same specific problems. Chapter 3 presents the proposed solution. First, the changes made to the HTR protocol and its messages, then a detailed description of each policy developed and implemented, and the scheme to allow the HTRScore adaptation, and some example scenarios to illustrate policy behavior and its expected results. Chapter 4 details the policies implementation scenarios for the NS-3 simulations and the evaluation process of the different proposed scenarios. All parameters used and metrics evaluated are shown in Chapter 4. Chapter 5 presents the evaluation of the results obtained with the simulations. Finally, Chapter 6 presents the conclusion of the dissertation, the challenges, contributions achieved by the proposed scheme and directions for future work.

CHAPTER 2 STATE OF THE ART

This chapter introduces the main concepts on which the work presented in this master dissertation is based. We introduce Mobile Ad hoc Networks (MANETs), their needs and characteristics. We also present the main routing protocols proposed to address MANETs’ needs, giving special emphasis on the Heterogeneous protocol HTR, on which this work is based upon. Policy-based context-aware routing concepts are also introduced. And finally, we present some background on policy-based management frameworks and related work on the specific topics the policies’ are focused.

2.1 C

2.1.1 INTRODUCTION

A mobile ad hoc network is a set of wirelessly connected nodes that do not depend on pre-defined infrastructures to communicate. MANETs are suitable for circumstances were a fixed infrastructure is not available or not reliable. Since MANETs do not rely on fixed infrastructures to exist, they are the solution of choice when it comes to emergency scenarios, rescue, military operations, and other scenarios where temporary communication and fast configuration is needed. MANETs are formed mainly by heterogeneous mobile devices with limited lifetime due to battery lifetime limitations. Each device that connects to a MANET act as a smart, self-configuring router, responsible for data dissemination and network creation, operation, management and control. The main characteristics of MANETs are: easy deployment and configuration, capacity for cooperation among nodes, simple infrastructure, limited resources, lack of centralized management, and unpredictable changes due to high mobility and context changes. These characteristics lead to communication and management challenges for building and maintaining such a dynamic environment working adequately.

2.1.2 ROUTING PROTOCOLS

2.1.2.1 DIJKSTRA’S ALGORITHM

Dijkstra’s algorithm [22], published in 1959, is a shortest path algorithm, which means it is able to find and prioritize shortest paths between two points for communication. It is a graph search algorithm that creates a shortest path tree, it attributes costs to links between devices and it finds, for a given node, the path with lowest cost to every possible destination.

First the Dijkstra assigns a distance value to every node, setting it to zero for all nodes initially and marking all nodes as unvisited and then it calculates the distance for every node.

For example, if the distance from A to B has cost 6 and from B to C the cost is 2, the distance value from A to C is 8. For each iteration the distances are calculated and recorded in the routing table and when the distance values change, the distance previously recorded is overwritten. Once the cost is calculated, the node is marked as visited and its cost will only be calculated again in the next iteration.

This algorithm is used as the basis of others routing protocols such as the Open Shortest Path First (OSPF) [23] protocol and others that we will further mention in this chapter.

2.1.2.2 ROUTING PROTOCOLS FOR MANETS

Due to such dynamicity introduced by MANETs, it is, up to nowadays, a challenge to develop efficient and flexible routing protocols, capable of addressing the ad hoc needs, without introducing a great amount of overhead. Routing protocols for MANETs were divided into three groups: proactive, reactive and hybrid protocols. Following we describe the main characteristics of each type.

With proactive routing protocols, nodes maintain routing tables with paths to each other destination node of the group or network. The update of routing tables is given through the dissemination of messages that share network information. Messages need to be constantly exchanged, since the network context may change leading to possible modifications in the paths. This transmission of messages, needed to keep the routing table updated, as well as the sharing of other information needed, can be very costly due to bandwidth and energy constraints.

The Optimized Link State Routing (OLSR) [24], proposed in 2001, is the most popular proactive routing protocol for MANETs. As in every proactive routing protocol, each node of a network running OLSR maintains routing tables and constantly exchange messages to share link-state information to manage such tables and share information. But OLSR reduces the amount of control messages disseminated in the network by introducing a mechanism called Multipoint Replaying (MPR). The MPR is not a new entity that is introduced in the network, but it is simply a role that specific devices will assume. Every node in the network choses a one-hop-neighbor node from which it can access more nodes that are two-hops away to act as their MPR node. An MPR node is responsible for efficient control messages dissemination because it restricts the number of nodes that retransmit control messages.

Reactive protocols, also known as on-demand protocols, do not keep routing tables or rely on message transmission to share network information with neighbors. The path is constructed on demand by flooding route requests messages (RREQ) only when needed and

depends on the resulting route request reply (RREP) sent by neighbor nodes. Because it does not exchange control messages constantly, the amount of overhead introduced to the network is reduced. Reactive protocols provide a greater advantage when the mobility ratio is not very high because the topology does not change so frequently, so RREPs are reliable. This is an advantage because without the need to transmit such update messages frequently, both bandwidth and energy are saved. The most commonly used reactive routing protocol for MANETs is the Ad hoc On-Demand Distance Vector (AODV) [25]. A noticeable particularity of AODV is that it introduces a destination sequence number for each route entry to avoid routing loops.

Hybrid protocols mix characteristics from both previous mentioned routing types for ad hoc networks to achieve a more dynamic approach hence promoting techniques that opportunistically can reduce overhead while proactively maintaining routing tables. Hybrid solutions often divide the network into groups, zones or clusters to achieve the mentioned objectives.

Although all this types of protocols provide good solutions for MANETs routing for they address different needs, there’s still a need for approaches to be adaptive. The context of MANETs is volatile, which means it can dynamically and unpredictably change the network needs.

2.1.2.3 AN ADAPTIVE ROUTING APPROACH

Each developed protocol performs better than the others depending on the network context, so an adaptive approach is needed for the nodes in order to adapt their behavior to meet the network needs that change dynamically, in a context-aware manner [26]. To address such goals, several adaptive protocols were proposed as well as different adaptive schemes to run over specific protocols. One of the proposed adaptive protocols, the one this work is based upon, is the Heterogeneous Routing Protocol (HTR) [20], a multi-path routing protocol for heterogeneous ad hoc networks based on the proactive protocol OLSR. HTR focuses on intelligent path computation and energy preservation through the use of the HTRScore information, a special metric which impacts on the path computation process. 2.1.2.3.1 THE HETEROGENEOUS ROUTING PROTOCOL (HTR)

First described in [20], HTR is a proactive cross layer routing protocol for heterogeneous mobile ad hoc networks. Heterogeneous, for HTR, means support is offered for devices with different interfaces that communicate via different technologies such as Wi-Fi, WiMax, Bluetooth or LTE. Routing is based on a modified version of the Dijkstra’s Algorithm, the Multipath Dijkstra, which stores multiple possible paths to a given destination. Multipath Dijkstra is introduced in [17].

The HTR creates an abstraction layer of the network by giving a unique IP address to each device even if it has multiple interfaces of different technologies. This unique address is the same until the node disconnects, this is assured by the Network Address Allocation Method [27].

Based on OLSR, the HTR also includes Multipoint Relays (MPRs), which are one-hop neighbor nodes selected to forward the traffic of control messages through the network for flooding control. MPRs are selected in such a way that a node can access every 2-hop neighbor and, in the HTR case, other metrics such as link condition and power efficiency are used in the MPR selection.

The original HTR terminology is presented in Table 1 and Figure 1 illustrates basic HTR characteristics. Both were originally published in [17].

Table 1: HTR Terminology

Node A MANET device which implements the HTR protocol as

specified in this document.

HTR interface Each interface of a network device which may have several interfaces, although the HTR attributes only one, unique, IP address to the whole node.

Neighbor node (1-hop neighbor)

A node which is a 1-hop neighbor of a given local node, if there is any local interface that has a direct link to at least one interface of this neighbor.

2-hop neighbor A node which is two hops away from another node and which can be reached (in terms of radio range) directly from at least one 1-hop neighbor.

Multipoint Relay (MPR) A node which is selected by a 1-hop neighbor, node X, as the forwarding node to retransmit a broadcast packet received from X if this one is not duplicated and has a “time to live” field greater than one.

MPR Set A (sub)set of neighbors selected in such a way that it covers (in terms of radio range) all symmetric strict 2-hop neighbors. Multipoint Relay selector

(MPR selector, MS)

A node which has selected its 1-hop neighbor as an MPR.

Link A node which is said to have a link to another node when one of its interfaces has a link to one of the interfaces of another Symmetric link A verified bi-directional link between two HTR interfaces. Asymmetric link A link between two HTR interfaces, verified in only one Symmetric 1-hop

neighborhood

The symmetric 1-hop neighborhood of any node X Symmetric 2-hop

neighborhood

The symmetric 2-hop neighborhood of X. HTR Terminology

X 1 1 1 1 2 2 2 2 2 2 2 2 1-hop neighbor of X 2-hop neighbor of X 1 2 Symmetric link Asymmetric link X 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 MPR of X

2-hop neighbor covered by a MPR MPR Selector Non MPR 1 1 1 1

Figure 1: HTR terminology (Source [17])

The HTR has some specifications, also presented in [17], which defines the protocol operation. Those are presented in

Table 2: HTR Features

HTR Features

Node addressing In HTR, each device has a unique IP address. HTR can use IP _{version 4 (IPv4) [7] and version 6 (IPv6) [8]} Link sensing

HTR keeps up-to-date information on which links exist between a node and its neighbors. The connectivity is checked through periodic emission of HELLO messages over the interfaces.

Neighbor discovery HTR allows nodes to discover its neighbors through the information exchanged during link sensing. Neighbor information is stored in the Link-Neighbor set repository. MPR selection and

MPR signaling

MPR selection and signaling provides flooding control by reducing redundant retransmissions. Each node select a subset of its 1-hop neighbors to retransmit broadcast packets.

Topology Control

message Are broadcasted so each node will be provided with sufficient link-state information to allow route calculation. Path computation With HTR, each node computes its routing table according to link quality information obtained through periodic message

exchanges.

HTR functionalities rely on two control messages that are sent periodically: HELLO and Topology Control (TC) messages. Link Sensing and Neighbor Discovery are the

functionalities that depend on HELLO messages, which are broadcasted through all interfaces carrying node information and checking link connectivity. The network topology accuracy is essential and since it relies on HELLO messages, and mobile ad hoc networks topology may change abruptly, they need to be sent in regular intervals to assure that the link remains active. HELLO messages are also responsible for carrying MPR information. TC messages are used for topology information advertisement, they are broadcasted by the MPRs and it contains the node that elected each MPR, which are called MPR selectors. The dissemination of TC messages by MPRs reaches all network nodes [78] and provides enough information to enable proper path computation. In addition, these control messages are also used to propagate human roles information associated to each network node, a feature we greatly explore in this dissertation.

The structure of a HTR packet, which holds HELLO and TC messages, is showed on Figure 2, while the structure of HELLO and TC messages are showed in Figure 3 and Figure 4, respectively.

Figure 2: Original packet format

Figure 3: Original HELLO message

0 1 2 3

Bits 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 HTR Header

Message

Time to Live Hop Count Message Sequence Number MESSAGE

Originator Address

Packet Lenght Packet Sequence Number Message Type Validity Message Size

0 1 2 3

0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1

Link Code Reserved Link Code Size

Neighbor IP Address HTRScore HTRScore Neighbor IP Address ... Neighbor IP Address HTRScore

Figure 4: Original TC message

These packets and messages are well defined and detailed in [17], here we simply show the structure because modifications were made and are showed and explained next in chapter 3.

2.1.2.3.2 HTRSCORE

Different from most routing protocols that consider only the hop count for path computation, HTR presents the HTRScore, a special metric that considers link capacity and energy conditions (battery level, residual energy). The HTRScore increases the duration of the network because it makes the protocol energy aware, distributing the traffic according to the residual energy of the nodes. It also considers packet loss probability, which depends on link stability. HTRScore is defined by the following formula (1).

Where ei, j, the transmission energy required for a node i to transmit an information

unit to its neighbor j; ρi, j, is the probability to lose a packet sent from i to j; Ri is the residual

energy of node i; and Ei is the initial battery energy of node i.

Parameters α, β, γ, and θ are non-negative weighting factors. If all weights are equal to zero, then the lowest-cost path is the shortest path. If γ and θ are equal to zero, the lowest cost path is the one that will require the least energy consumption, considering retransmission or not, also regarding the value of β. If γ is equal to θ then the normalized residual energy is used, while if only θ is equal to zero, the absolute residual energy is used. Links with higher HTRScore values are less likely to be chosen as an alternative path to a destination. Specifically in the HTR, the selection of MPRs also involves the HTRScore of

0 1 2 3

0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 Reserved

Advertised Neighbor IP Address HTRScore

Network Address from Gateway ANSN

Network Information from Gateway ...

Network Address from Gateway Network Information from Gateway

Advertised Neighbor IP Address HTRScore

each link.

Each node disseminates, via HELLO message, its cost to forward packets to its neighbors. So, when a policy is activated, incrementing the HTRScore of a node, other nodes will know that sending information through a node with higher HTRScore is not cost-effective and will search for neighbors with lower costs.

2.1.3

If a network event meets a predetermined condition, this event will activate a predefined action. This set event-condition-action defines the basic elements of a policy, although events and conditions are optional because a policy action can be immediately executed in the network. Policy implementation is defined by a framework called Policy-Based Network Management (PBNM) [28].

PBNM is a solution that aims at optimizing network behavior by allowing nodes to make autonomic decisions based on rules that can be applied to a specific node or specific set of nodes. Policies can guide the network configuration, operation and management supporting network functionalities, such as load balancing and monitoring, to work in an autonomic manner based on network events, reducing human intervention. In policy-based systems, network administrators enter high level requirements as policies in the system and these are translated to low level policies.

In 2001, the IETF released the RFC 3198 [29] with the terminology for Policy-Based Management, describing its main components: a Policy Decision Point (PDP), responsible for making policy decisions, interpretation and translation for itself and other nodes, it evaluates the rules and triggers the respective actions; the Policy Enforcement Point (PEP), responsible for the execution of a policy decision; and the Policy Repository, a database where all policies are stored. With these main components it is possible to apply a consistent policy-based management framework to networks.

The events that trigger a policy may be a change in the network context, which often happens in MANETs. So, to gather, manage and interpret context information, it is crucial to know the network state beforehand. Context information of ad hoc networks may include mobility ratio, battery level, device capacity, available bandwidth, time, location, among others. As shown following in this chapter, different context management schemes were proposed, some using sensors to gather external context information, other using intelligent agents to monitor the system and gather such information.

Policy-based context-aware communication schemes are very popular for mobile ad hoc networks since they allow autonomic management and flexible adaptation for network devices to address networks’ requirements. As such, long term communication can be

maintained even on highly dynamic environments such as MANETs. Related work on policy-based context-aware management and adaptive schemes for MANETs is detailed on the next subsection.

2.1.3.1 ORGANIZATION BASED ACCESS CONTROL

Because MANETs are usually formed by different groups of people, we decide to take into consideration the role users perform within an organization to guide routing through the implementation of policies.

When it comes to security management systems, Access Control models are a very popular approach. Several models have been proposed such as Discretionary Access Control (DAC) [30], Task-based Authorization Control (TBAC) [31] and Role-based Access Control (RBAC) [32][33]. RBAC is a very popular model [4] because it allows permission to be given according to roles, and not specified for each user a time as the traditional approach. With RBAC, network administrators specify the association between users’ roles and the network nodes to define how the access control will happen. RBAC simplifies the specification of permission increasing security flexibility, since it is easy to administrate the change and adaptation of such permissions with it.

But although its benefits brought significant changes, these models has limitations when applying policies to an organization that needs context to apply policies, also they only work with denial and permission, there’s no obligations or recommendations. Because of these limitations another different models were proposed and one of them is specific organization-oriented, which means the specification of the policy is completely parameterized by the organization, it is called the Organization Based Access Control (OrBAC) [34].

Although RBAC is a popular approach for security applications among MANETs, the OrBAC was chosen as the model to represent the policies in this dissertation since our solution is also organization-based, which fits to OrBAC’s proposal. The OrBAC model defines a relationship between organizations, subjects (roles), objects (views), action (activity), context and context violation (for obligation policies only).

In the OrBAC paper [34], the authors define organization as a group of activity entities like a hospital, an office, a department. Subject are active entities such as users or organization (for example, a department of an organization) and roles is what links subjects to organizations. For example, subject user John is a doctor (role) from the organization South Hospital. Objects are defined inactive entities like medical records or administrative processes, and view defines how these objects relate to the other parameters. Actions refer to the policy action itself while activity is the general activity that will lead to this action. Finally,

context are circumstances that need to happen in order to activate the action. Context violation is another type of context, used in obligation policies that defines the events that will prevent the action. In the OrBAC model, a permission would be defined in the following way:

Permission (organization, role, activity, view, context) Permission (hospital, doctors, read, medical record, surgery) Meaning that, doctors from the hospital are allowed to read medical records, in case of surgery. Since our policies relate to specific network policies that consider the roles users’ play, our policies follow the same definition but with more network-related characteristics. Although we don’t use the whole OrBAC framework possibilities, we use the concepts to represent different policies and apply these policies to different groups according to business needs.

2.2 R

W

In this section we present Related Work on other policy based network management schemes developed to meet the requirements of different scenarios. Also, we present related work on energy reduction and load balance techniques for MANETs, since it is also an objective of this dissertation, to provide effective solution for these problems.

2.2.1 POLICY MANAGEMENT FRAMEWORKS

In the last few years, several context-aware and policy-based management solutions have been proposed for mobile ad hoc communication. Although the majority of them just explore the theoretic possibilities of bringing these two concepts together, only a few provide consistent results of this application. As such, it can be, to this day, considered an open area of research.

Based context aware applications for MANETs, ACAN [35], which stands for Ad Hoc Context Aware Network, was created. ACAN is a specific architecture for MANETs that relies on physical and network sensors to gather information such as location, time, bandwidth, delay, etc. In their first paper the authors define the architecture, the protocol stack and detail the service discovery process.

In the subsequent extension [6] that ACAN was simulated and evaluated, only terms of service discovery, access and availability were considered, nothing in terms of energy consumption or impact on network metrics (delay, jitter, throughput) was evaluated. And although location was considered as context, nothing regarding network nodes roles or other information was taken into account. The objective was to evaluate the efficiency of the sensor

agents in detecting and answering a service request depending on the request rate. As expected, the higher the request rate (tests with more than one request per second), the higher the time it took to detect context changes. When comparing the solution with and without context detection, the average detection time increases when the number and frequency of request rates increase and no context information is considered.

Combining context-awareness with policy-based management, the paper [36] proposes a hybrid network organization, in a hierarchical yet distributed manner along with a context model to gather and manage environment’s information. The authors created a scheme based on modules and roles. Modules are preinstalled software that comes within the nodes and consider the physical attributes of the device. Roles, on the other hand, depend only on the organizational role attributes. Roles can be Cluster Nodes, Cluster Managers or Cluster Heads and define the formation hyper-clusters along with context information. Cluster Managers are chosen according to the Capability Function, a function based on memory, processing and battery power, computer load, mobility ratio and time which denote the physical capability of a device. In this work the authors also propose a Distributed Policy Repository with a policy-based distribution scheme so the policies are still available to all nodes even in case one repository is lost. In [13], an extension of [36], the authors explore expansively the context-aware procedure, a key feature of the solution since the process depends on the context information to react. They propose a context model that details context, sensors and their relationship and a method to disseminate context information to manager nodes. These features aim at optimizing context management by aggregating context information and disseminating only average values and defining thresholds that context have to achieve before being disseminating to avoid unnecessary information transmission and processing.

The context-aware platform proposed, follows PBNM concepts as it introduces a Context Collection Point (CCP), for context gathering; a Context Decision Point (CDP) that monitors and interacts with the CCP and also to the PDP; a Context Repository, where context information is stored; and a Context Management Tool, which runs on the Manager Node and interacts with the Policy Management Tool and Policy Decision Point to check for changes needed. This extension also introduces an adaptation loop, which initiates with the deployment of policies that leads to context gathering that leads to the activation of other policies. The objective of this adaptation loop is increase network autonomy allowing self-configuration and self-optimization features. [37] is another work from the authors of [36]. In [37], they evaluate the time spent to retrieve, set and delete a policy from the distributed repository proposed in[36]. Results show that the distributed scheme introduces a great deal of overhead in the network but it optimizes the policy access time.

To address security needs, the PEACE framework [38] was developed. PEACE describes ad hoc networks as communities and their specification is called doctrine. Roles and policies define how the bootstrap process, management and the access to services occur in a secure way. Besides roles and policies, for security reasons the information model also implements, for each doctrine, public keys to assure users identity and a signature. The results of PEACE aim to find the probability of a community to end up in static state, which means when the community can no longer be reconstructed because users are out of range and can no longer receive reconstruction messages, the messages responsible to maintain the community alive.

The extension of PEACE [38] proposes the separation of policies into obligation and authorization policies, which guides roles interaction, which are currently divided into management and application roles, to allow flexibility while including dynamically new roles to the community. As in [38], in [39] the focus is security and they also improved the security management scheme to support authentication, through node that assumes a role responsible for node validation; membership management, through a role that reports to other nodes the network topology changes, for example, if a node disconnect; and access control policies that states which actions a node is allowed to apply in the network and how. The scenario chosen for implementation in this work was comprised of robots with a video camera and sensors for context gathering but the mere evaluation made was the measurement of the time taken to deploy the policies and also the whole assignment of roles and related policies process.

With regard to military scenarios, another framework [14] was developed for ad hoc networks. Developed for the Army CERDEC DRAMA (Dynamic Re-Addressing and Management for the Army) program, [14] presents a hierarchical policy-based model solution for network management. Similar to [40], this solution organizes the network in a hierarchical structure but, instead of clusters, it divides the network into policy domains on which policies specific policies can be applied. The proposed framework was implemented on a test bed comprised of two ad hoc routing domains, both running OLSR and connected through a wired backbone. Although it has been demonstrated on a real scenario, [14] relies on physical servers for mobility and QoS management to work. Simulation were performed to measure the solution overhead and the SIP (used to handle mobility) response time, results are shown in [41].

The extension described in [42] includes Policy Based Network Security capabilities to improve security through the inclusion of an Intrusion Detection System (IDS) that, by the dissemination of messages, reports if policy agents are classified as “trusted” or “malicious”; and a secure distributed policy scheme through authentication.

Authors in [43] propose the Hierarchical Cross Layer Protocol (HCLP) to manage group communications in ad hoc networks. HLCP takes in consideration the heterogeneity of nodes and their physical distance to calculate paths. A policy was defined to decide, based mainly on distance, whether to use a gossip-based [44] or a tree-based [45] technique to avoid overhead, while still improving reliability, which are two very important aspects of MANETs. In this work, nodes have two possible roles: Super Node or Leaf Node. The decision process is defined through an election policy that aims at sparing the resources of less capable devices.

Similarly to [40], in [43] there is a function to determine node capability based on its physical characteristics. This function serves as input for the election policy. Simulations were run on NS-2 [46] and the scenario was a MANET with the amount of nodes varying between 60 and 110, within an area of 1500m*1500m and simulation time of 1000s. The HCLP is compared with the gossip technique and the delivery rate and the overhead of both solutions are analyzed, as well as the protocol performance impact while varying group size, node density, moving speed and propagation distance. HCLP introduces lower overhead, half of it in most cases, than the gossip protocol in all four cases, which shows the remarkable advantage of HCLP. In terms of packet delivery rate, both protocols show good results with HCLP showing very similar results to the gossip protocol, outperforming it a bit in some cases. Although a reliable and cost-effective protocol, HCLP does not consider the energy consumption on its framework, which is a design flaw since energy is one of the most important parameters in MANETs.

The idea is that the protocol allows nodes to have different modes of operation to adapt to network changes according to context information gathered by a monitoring agent. The authors defend that solutions that propose adaptation by changing the routing protocol according to the network needs, as it is proposed in [47] and [36], may cause service discontinuity, so they propose the multi-mode model, therefore, each device can assume specific characteristics at any time needed. Mode 1 defines that the node should establish routes reactively and that is a requirement for all network nodes to have Mode 1; Mode 2 allows the creation of clusters, groups exchange routes through the propagation of distance vectors; Mode 3 is proactive, nodes announce their location. Such proactive adaptations are performed by varying time-to-live values.

The switch between modes depends on the network context such as mobility, traffic load, and network density. The node that want to switch its mode, changes its own routing table and then propagate the update to its neighbors (if the alteration is to a proactive mode),further details can be found in [26]. The authors claim that simulations results showed that a node can change between modes while still keeping consistent the routing

tables. To evaluate the multi-mode adaptive scheme, two scenarios were simulated using GloMoSim [48]: a static scenario, were nodes switches mode randomly comprised by 36 802.11b nodes in a grid topology and a mobile with fixed nodes scenario, also with 36 nodes, this time moving at fixed speed.

The simulations evaluate the mode switching frequency in terms of packet delivery ratio, end-to-end delay, and routing control packets and compare the adaptive multi-mode with the proactive-only mode and reactive, for 10 and 20 simultaneous source of traffic. Results shows that with up to 10 simultaneous traffic sources when mode switches less than four times per minute, the adaptive method outperforms the reactive mode for packet delivery; for end-to-end delay, the proactive mode also outperforms the other two, but if the switching between modes is less than 36 per minute; the reactive mode outperforms the others when measuring control packets because it does not send any, but the more the switching times, the higher the amount of control packets. When there are 20 simultaneous sources, the end-to-end delay is even higher than the reactive mode, with no significant change in the packet delivery rate or in the amount of control packets exchanged.

The simulations of the second scenario analyze the packet delivery ratio and routing control packets while varying the speed of the devices and the amount of nodes in each mode. The mode distribution does not impact on the packet delivery ratio and the higher the movement speed of the nodes, the lower the packet delivery ratio. Finally, a simulation to compare the protocols (reactive, proactive and adaptive), while changing network context was performed. When evaluating packet delivery ratio, the adaptive protocol showed similar results to the proactive protocol. The adaptive protocol also outperformed the other two by showing that is sends less control packets per data packet delivered than the other two even when context changes. The work performed in [26] is very interesting and close to what our work proposes, since we seek an adaptive behavior of the network communication, but ours focuses on the adaptive behavior through policies.

2.2.2 ENERGY REDUCTION TECHNIQUES

Batteries are very limited resources and the concern with their preservation when it comes to MANETs is not new, there are works since the early 2000s focusing on extending the lifetime of mobile ad hoc devices [49], [50].

Authors in [51] point out that on demand protocols are more energy efficient due to their reactive nature and suggest a routing scheme based on AODV [52] with the modifications proposed in [53]. The scheme considers 3 levels of battery: when there is more than 50% of the battery which is called Active Mode; when it is between 50% and 20% the device is considered to be in a Critical State; when it has less than 20% of energy, this is seen

as being in the Danger State. When a device receives a Route Request Message (RREQ) it proceeds according to the following condition test:

If En > ETh&& T - T(N ) < DS

A reply message ACTI VE_REP containing the route length is sent Else if En < ETh

No reply is sent

Meaning that if the energy level of the node receiving the RREQ message is greater than the threshold defined (based on the levels describe before) and subtracting T(N) (time the last packet has been forwarded) by T (current time) is less than DS (current estimated distance between nodes), the node responds the RREQ message, otherwise, no response is sent. This scheme was implemented on the NS-2 public simulator tool with different scenarios for 20, 50 and 100 nodes in an area of 1000 x 750m. The implementation parameters are: transmission power of 0.2818W, power consumption for transmission of 1.6W and 1.2W for reception, a threshold of 10db, a 1mpbs of data rate, 200mt of transmission range, and packet size of 512 bytes.

Four cases are evaluated within these scenarios and compared with DSR. The first case evaluates the energy consumption of a network with 50 nodes with the number of sources varying between 10 and 45 and the pause time is of 0 seconds (maximum mobility). The results show that despite the obtained close values, AODV consumes less energy than DSR except when the number of sources is between 25 and 35. The second case is exactly similar to the first one except for the pause time which in this case is of 500 seconds. In this case the DSR consumes even more energy than AODV when compared to the first case. This indicates that for scenarios with less mobility, AODV performs better. The third case has the same configuration of the first one but it evaluates the number of exhausted nodes and it was observed that, at the end of the simulation, 74% of the AODV nodes died, in contrast to the 78% of the DSR. The fourth case is similar to the second scenario but, as in the third one, the number of exhausted nodes is evaluated and 49% of the AODV nodes died, against the 52.34% in the DSR case. In terms of node exhaustion, the proposed scheme did not seem to increase in a very effective way the lifetime of nodes.

Other results for the scheme proposed in [51] are presented in [54]. In this paper, the scheme is also applied to DSR and is tested with UDP and TCP connections. The modified DSR is called EDSR and the modified AODV is called EAODV, the letter E stands for Energy here. This paper also introduces another detail to the scheme: if the requesting node does not receive any replies, the closest neighbor is selected for forwarding data. Packet delivery ratio is measured and taken as a metric while varying the pause time and node speed. As in [51], the proposed scheme showed very similar results in terms of packet delivery to the original

non extended protocols in both TCP and UDP cases, but there are no results in terms of energy to prove the efficiency in terms of energy saving.

Another recent proposed adaptation for the AODV protocol, called MECB-AODV [12], focuses on prolonging communication by maintaining the energy of intermediate nodes for as long as possible. It is very similar to the scheme presented in [51]. It adds a step in the request process that makes the node check its neighbors’ energy level information and compare it to a predetermined threshold and, if it meets the threshold, rejects the RREQ. The difference from the MECB-AODV is that, if the requesting node does not receive any replies, its neighbors must discover which of their neighbors has more remaining energy and this is used as a criterion. A scenario of 21 nodes was implemented using the NS-2 simulation tool within an area of 1500m², 2mbps bandwidth and initial energy of 1000J lasting 40s simulations. The MECB-AODV was compared with pure AODV in terms of overhead, packet delivery and energy consumed. Although it outperforms the AODV in terms of packet delivery and energy consumption, the small number of simulations and results are not enough to guarantee a better quality for this solution.

For proactive routing protocols, a modification was proposed to the OLSR in [55] called Energy Aware OLSR, OLSR_EA. In this solution, each node measures its own energy level at regular intervals and based on this information, it makes a prediction of energy consumption for future intervals used to calculate modes energy cost. The value of the energy cost is used as a metric for route computation by a proposed modified version of Dijkstra. OLSR_AE was implemented on the ns-2 to simulate its effectiveness over OLSR. For all the evaluated cases, varying transmission power (heterogeneous and homogeneous) and packet rate, the OLSR_AE showed better results than the OLSR.

As showed in this section, there are interesting approaches used to extend the lifetime of ad hoc networks through energy aware path computation processes but, to the best of our knowledge, no solution is focused on the benefits of groups based on human roles. Our solution applies policies in the network to achieve an intelligent and adaptive solution to prioritize the energy preservation a predetermined group based on its human role and formation over the HTR routing protocol.

To address the need for an adaptive solution that takes into account a human role and its hierarchy, we introduce a set of policies named Keep Energy (KE).

2.2.3 LOAD BALANCE TECHNIQUES

A very recent publication [56] proposes a load balancing scheme to the preemptive DSR (PDSR), a modification to the reactive DSR protocol. The preemptive scheme gives support to high mobility scenarios because intermediate nodes send a warning telling the

node might disconnect when the signal strength falls below a threshold so source nodes can chose another path to communicate. Also, in the route discovery phase, the destination node sends the Route Replies (RREP) messages including multiple paths. The load balancing scheme proposed works through route selection based on the energy level of nodes. The PDSR is compared with the DSR and results show a slightly increase in the packet delivery rate, and, as the existing DSR, loses performance in high mobility scenarios. In terms of delay the PDSR also shows better results and increases when mobility is higher. The HTRScore naturally considers the energy level of nodes for route selection, our load balancing scheme adds the current load of the node to the calculation.

Another approach for reactive protocols is presented in [57], a Node Centric Load Balancing Routing Protocol (NCLBRP), based on the AODV. They divide the nodes into 3 different roles based on its interaction with other nodes: terminal nodes are connected to the network through one link only; trunk nodes connect network segments; normal nodes are all nodes that are not characterized as trunk or terminal. The congestion status of the node is determined by its queue size and when it reaches a threshold it stops responding to route requests, unless the request is from a terminal node. Simulations on ns-2 compared the NCLBRP with the AODV in a simulation area of 1000x600 meters, the number of nodes varying from 50 to 100, 20 of them transmitting data with 2Mbps bandwidth, and simulation time of 100 seconds. Two metrics were evaluated, the average delay and the normalized routing load, which is the average number of routing control packets per data packet delivered. Results are very similar for both protocols with NCLBRP presenting lower average delay and amount of routing control packets. Authors say load balancing is achieved successfully. The idea of not responding to a route request is original and efficient, but if all the neighboring nodes are congested, it would take a longer time to send packets, which is avoided in our solution for it is based on a proactive protocol.

The main problem load balancing tries to address is that, usually, the flow is concentrated on the most cost effective nodes of the network, which usually are the central nodes. The paper [58] focuses on this problem, on shortest path routing algorithms, because they concentrate the data flow on network central nodes. It presents solutions for both reactive and proactive protocols, focusing on AODV and OLSR, respectively. For OLSR, they propose a new method to fill the routing tables and select the next hop according to the number of MPR Selectors of each node. The authors refer to Pham and Perreau’s results in [59] to affirm central nodes are the ones with more MPR Selectors and select the nodes with less MPR Selectors as the next hop to reach a destination, distributing the traffic among more nodes.

and although it also shows some concentration on central nodes, OLSR with load balancing distributes the traffic more evenly among network nodes in both pause times of 100s and 700s. The solution also increases packet delivery because it avoids congested nodes. Also an interesting idea, to choose nodes with less MPR Selectors, but our solution outstands this because of the HTRScore, which also influences the MPR Selector and the policy that considers the current load.

2.3

CHAPTER SUMMARY

In this chapter, we introduced the fundamental basis this dissertation: MANET’s concepts and the main routing protocols developed, specially the HTR, on which the work in this dissertation is based. Also, we introduced policy based management models and context-aware concepts. Finally, we present related work on policy based solutions and energy reduction and load balance techniques.

To add efforts to the objective of finding optimized adaptive solutions for MANETs, we propose sets of policies to improve routing behavior. In the following chapter we present the solution proposed with four study cases detailing each policy.