Clustering in wirelesssensornetworks is one of the crucial methods for increasing of network lifetime. The network characteristics of existing classical clustering protocols for wirelesssensor network are homogeneous. Clustering protocols fail to maintain the stability of the system, especially when nodes are heterogeneous. We have seen that the behavior of Heterogeneous-Hierarchical Energy Aware Routing Protocol (H-HEARP) becomes very unstable once the first node dies, especially in the presence of node heterogeneity. In this paper we assume a newclusteringprotocol whose network characteristics is heterogeneous for prolonging of network lifetime. The computer simulation results demonstrate that the proposed clustering algorithm outperforms than other clustering algorithms in terms of the time interval before the death of the ﬁrst node (we refer to as stability period). The simulation results also show the high performance of the proposed clustering algorithm for higher values of extra energy brought by more powerful nodes.
One of the most important factors in wirelesssensornetworks is energy consumption, hence the lifetime of these networks are strongly depending on remaining energy in the nodes. According to sensors placement farness and wireless communication between them, it is necessary to optimally consume the energy in these networks. In this study a hybrid approach is proposed by mixing two existing protocols, namely flat multi-hop routing and hierarchical multi-hop routing. Also by using Cellular Learning Automata (CLA) as clustering technique, the energy in the network will be managed and finally the lifetime of nodes will be increased. Mathematical simulation and analysis show a good performance of clustered hybrid model for energy saving that in compare with multi hop routing algorithm and hierarchical routing in non-clustered and clustered conditions, the lifetime increasing are 10.39%, 27.36% and 5.57%, 23.83% respectively. Keywords: Lifetime, WirelessSensorNetworks, Flat Routing Protocol, Hierarchical Routing Protocol, Hole problem .
WirelessSensorNetworks (WSNs) is a network of an inexpensive low coverage, sensing, and computation nodes. The foremost difference between the WSN and the traditional wirelessnetworks is that sensors are extremely sensitive to energy consumption. Energy saving is the crucial issue in designing the wirelesssensornetworks. Many researchers have focused only on developing energy efficient protocols for continuous-driven clustered sensornetworks. In this paper, we propose a modified algorithm for Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Our modified protocol called “Energy-Efficient Adaptive Protocol for Clustered WirelessSensorNetworks (EEAP)” is aimed at prolonging the lifetime of the sensornetworks by balancing the energy consumption of the nodes. EEAP makes the high residual energy node to become a cluster-head. The elector nodes are used to collect the energy information of the nearest sensor nodes and select the cluster-heads. We compare the performance of our E E A P algorithm with the LEACH protocol using simulations.
In this paper, we presented a new objective for maximizing the network lifetime using ACO-MNCC algorithm to increase network lifetime and balance the node power consumption and as long as possible. The idea behind the ACO-MNCC is simple using the lowest energy path always is not necessarily best for the long- term health of the network, because it would cause the optimal path quickly get energy depleted. The approach searches for the optimal solution by always pursuing one more connected cover than the best-so- far solution. This way, the approach not only avoids building excessive subsets but also improves the search efficiency by setting an explicit goal for the ants. Pheromone and heuristic information are also designed to accelerate the search process for prolonging the network lifetime. ACO-MNCC is a promising method for prolonging the lifetime of heterogeneous WSNs. Extensive simulation result clearly shows that the proposed approach provides more approximate, effective and efficient way for maximizing the lifetime of heterogeneouswirelesssensornetworks.
the field of developing hard ware, software, designing architectures and network protocols for sensornetworks. To increase effective lifetime of sensor network, energy efficiency should be considered in all aspects of designing sensornetworks. Organizing nodes in separate groups for preventing extra data transfer is a method for reducing nodes' energy consumption but on the other hand the problem of clustering is that cluster heads requiring operations such as gathering data from other nodes and their aggregation and sending them to base station have the most energy consumption so some protocols are suggested to overcome this problem in which by Intermittent change of cluster heads the amount of consumed energy is distributed in a cluster and Workload and the most energy consumption won't be limited to aggregate nodes or cluster heads. On the other hand, based on their application wirelesssensor network nodes are arranged in the environment randomly and without exact engineering and scheduling and network topology is continuously changed due to Node failures, node Damaged, adding new nodes to the network node energy drain or channel fading so we should also consider this condition that in some applications organizing nodes in Fixed and static clusters without considering network dynamism make designed protocols impractical and useless. Therefore in designing protocol for wirelesssensornetworks some arrangements should be considered in this field.
Kumar  suggested and tested two novel clustering-based algorithms for heterogeneouswirelesssensornetworks that are known as Single-Hop Energy- Efficient ClusteringProtocol (S-EECP) as well as Multi-Hop Energy-Efficient ClusteringProtocol (M-EECP). In the former, CHs are chosen by weighted probabilities on the basis of ratios between remaining energy in every node as well as average energy of the network. Nodes with great amounts of initial energy as well as remaining energy are more likely to be chosen as CHs than those with lesser energy while in the latter, the chosen CHs transmitted the information packets to base stations through multi-hop transmission method. Network lifetime was studied and simulations revealed that the suggested algorithm extended network lifetime apart from achieving load balancing amongst CHs.
The performance requirement of a network is always different under various application situations. For example, in the situation of using a wirelesssensor network to monitor the fire in a forest, the network should keep its nodes to work as long as possible. Therefore, energy saving is a key task to extend the lifetime of the network. In this case, during normal monitoring process, most devices could be turned into the sleep mode and only a few devices work regularly in order to decrease the energy consumption. In case of detecting the fire, the network is required to operate with high throughput and reliably. Therefore, the routing protocols of such a wirelesssensor network need to be adapted to the application, which means the routing protocol should be dynamic.
In wirelesssensor network, it is an important task to collect the data periodically from various sensors node for monitoring and recording the physical conditions of the environment. The sensed data must be transmitted and received between the nodes in the network. The Low Energy Adaptive clustering hierarchy (LEACH) is one of the routing protocol to transmit the data between the nodes in the network. In this work, LEACH protocol is modified and developed the new concept called MLEACH. The proposed protocol is energy efficient for heterogeneous network. The performance was analyzed by considering the time period and it shows that the number of alive nodes was less. Since the alive node is less the energy consumption is also less and thereby increasing the energy efficiency of the network. The comparative analysis was made between the existing and the proposed method. Simulation result shows that the proposed method is more energy efficient than the existing LEACH protocol.
A Stable Election Protocol) protocol was used to improve the LEACH protocol. It provides heterogeneity in the wirelesssensornetworks. This protocol provides LEACH like operation but this protocol has two different level of energy. Two tier clustering is used in SEP. in this approach, cluster head election is randomly selected and distributed based on the fraction of energy of each node assuring a uniform use of the nodes energy. SEP based on weighted election probabilities of each node to become cluster head according to their respective energy. In this some NCG are selected as cluster head and others as gateways. IB-LEACH distributes the energy load evenly among various sensor nodes. IB_LEACH is a self-organizing, adaptive clusteringprotocol. It does randomized rotation of the high-energy cluster-head position in such a way that various sensor nodes drain the energy from a single sensor. At any time sensor nodes can elect themselves to be a gateway. Base station confirms gateway nodes whether the node elected are suitable for gateway or not. Gateway nodes or cluster head nodes broadcast their status via advertisement message (ADV) to the other sensor nodes in the network. Non gateway nodes can also elect themselves as a cluster head with a certain probability. These cluster head nodes broadcast their status via advertisement message (ADV) to the other sensor nodes in the network.
The assumption of homogeneous nodes does not always hold in practice since even devices of the same type may have slightly different maximal transmission power. There also exist heterogeneouswirelessnetworks in which devices have dramatically different capabilities, for instance, the communication network in the Future Combat System which involves wireless devices on soldiers, vehicles and UAVs. In contrast to a traditional static wirelesssensor network which consists of a large number of small sensor nodes with low computational, storage and communication capabilities, such limitations no longer apply in a mobile sensor network. In  the use of vehicles as sensors in a “vehicular sensor network,” a new network paradigm that is critical for gathering valuable information in urban environments is studied. However, existing routing protocols for WSNs are built on the network architecture (called flat architecture) such that all sensor nodes are homogeneous and send their data to a single sink
LEACH protocol homogeneously allocates the energy in the sensor node. While the heterogeneoussensor nodes consist of different capabilities of different energy levels. For a homogeneous sensornetworks energy levels, sensing range and computational power are considered to be the same. In the case of heterogeneous network each node has different capabilities in different aspects. Cluster head consumes lot of energy when compared to the non-cluster head node. This makes the cluster head to die soon. LEACH is a kind of cluster based routing protocols which is maximum used for cluster formation in a distributed network.LEACH randomly selects the cluster head and rotates this role to evenly distribute the energy among the sensors in the network.All the nodes other than the cluster heads communicate with the cluster head in a TDMA fashion.Sensor nodes typically use irreplaceable power with the limited capacity, the nodes Capacity of computing, communicating, and storage is very limited, which requires WSN Protocols need to conserve energy as the main objective of maximizing the network lifetime. An energy-efficient communication protocol called LEACH, conserves energy by changing the cluster Head periodically and also clusters members.
Abstract – In recent times, wirelesssensornetworks (WSNs) have become progressively more attractive and have found their way into a wide variety of applications and systems because of their low cost, self-organizing behavior, and sensing ability in harsh environments. A WSN is a collection of nodes organized into a network. Routing is a vital technology in WSNs and can be roughly divided into two categories: flat routing and hierarchical routing. In a flat routing topology, all nodes have identical functionality and carry out the same task in the network. Nodes in a hierarchical topology do different tasks in WSNs and are usually arranged into clusters. We analyze a fuzzy clustering algorithm (FCA) which aims to prolong the lifetime of WSNs. This algorithm adjusts the cluster-head radius considering the residual energy and distance to the base station parameters of the sensor nodes. This helps to decrease the intra-cluster work of the sensor nodes, which are closer to the base station or have lower battery level. Fuzzy logic is utilized for handling the uncertainties in cluster-head radius estimation. We compare this algorithm with the low energy adaptive clustering hierarchy (LEACH) algorithm according to the parameters of first node dies half of the nodes alive and energy-efficiency metrics. Therefore, the FCA is a stable and energy-efficient clustering algorithm.
Hinzelmann proposed a hierarchical routing algorithm for sensornetworks called LEACH [7, 9]. LEACH is one of the most popular hierarchical routing algorithms for sensornetworks. It is a clusteringprotocol consisting of distributed data of clusters. LEACH selects some of the sensors randomly as the head cluster (CH) and distributes energy among them. The idea is that node clustering is done based on received signal power and head clusters are using as routing to sinks. As a consequence, energy will be saved because, instead of all nodes, only head clusters do transmission. LEACH is completely distributed and doesn't need information throughout the network. However, LEACH is using single hop routing in which every node can send data directly to head cluster and base station. An Optimal number for head cluster is almost 5% of whole nodes. Processing data such as data releasing and aggregating is done locally in head clusters. Head clusters change randomly to balance energy dissipation in nodes. A random number (Integer), r will be selected between 1 and 0. A node could be current round's head cluster only if its number is below the threshold value.
To preserve the functional lifetime of all sources and efficient utilization of the energy of the source nodes, a Decentralized life maximizing tree construction algorithm  was studied, the DLMT  constructs a tree by selecting highest residual energy parent node to act as a center of data aggregation. The DLMT  construction algorithm arranges all nodes in a way that each parent will have the maximal-available energy resources to receive data from all of its children. Such arrangement extends the time to refresh the tree and lowers the amount of data lost due to a broken tree link before the tree reconstructions. The DLMT  algorithm can be further improved by considering distance also as a factor. In the proposed method we also include distance between the sensor nodes. Transmission distance has a major impact on the working of sensor network because the required power of wireless transmission is proportional to the square of the transmission distance. We follow the approach of clustering of nodes based on EM  algorithm. The EM algorithm includes minimizing the sum of the squares of the distances between nodes and cluster centroids. Therefore, we use the EM  algorithm to group the WSN nodes into K clusters on the basis of distance. We apply the concept of EM  algorithm initially and then use a new form of decentralized life maximizing tree, DLMT  algorithm accordingly. The cluster formed using the EMD algorithm goes through our proposed algorithm called Decentralized Lifetime Maximizing Tree using Clustering based energy and distance (DMLTC), which creates trees within the clusters already created .The choice of the tree is based on the minimum distance of the sub-sink from the sink.
According to existed protocols, using wireless channels is based on Media Access Control (MAC) protocols which allocate wireless resources and control the way that sensors access a shared radio channel to communicate with their neighbours. When designing a MAC protocol for a WSN, main considerations should be: energy efficiency, propagation delay, network scalability, throughput, fairness, and bandwidth utilization. Among them, energy consumption is usually the most important one. So it is necessary to find and analyze the reasons that cause energy loss. In general, sensors’ ineffective energy consumption can be summarized as: protocol overhead, collisions, overhearing, and idle listening. Some early papers are most designed by adding dormancy mechanisms suitable for WSN. Many of later papers are built upon those, and make improvement and optimization on the factors above.
Key establishment: Establishment of keys in sensornetworks can also be realized with protocols where the nodes set up a shared secret key after deployment, either through key transport or key agreement. The advantage of key agreement over key transport is that no entity can predetermine the resulting key as it depends on the input of all participants. There are three types of general key agreement schemes: 1.trusted- server schemes, 2.self-enforcing scheme and 3.key pre- distribution scheme. First the Trusted server scheme
The energy model represents the level of energy in a wireless node. There is only a single class variable energy which represents the level of energy in the node at any given time. The energy model in a node has a initial value which is the level of energy the node has at the beginning of the simulation. This is known as initialEnergy. The constructor EnergyModel(initialEnergy) requires the initial-energy to be passed along as a param- eter. It also has a given energy usage for every frame it transmits and receives. These are called txP ower and rxP ower. These parameters units are represented in table 2.5 and the default values defined by the NS-2 developers. When the energy level at the node goes down to zero, the value in energy variable, no more packets can be received or trans- mitted by the node. The energy model in NS-2 only models the power consumed by the
WSNs (WirelessSensorNetworks) is an emerging area of research. Researchers worldwide are working on the issues faced by sensor nodes. Communication has been a major issue in wirelessnetworks and the problem is manifolds in WSNs because of the limited resources. The routing protocol in such networks plays a pivotal role, as an effective routing protocol could significantly reduce the energy consumed in transmitting and receiving data packets throughout a network. In this paper the performance of SVR (Spatial Vector Routing) an energy efficient, location aware routing protocol is compared with the existing location aware protocols. The results from the simulation trials show the performance of SVR.
DODAG Information Object (DIO): the DIO message is mapped to 0x01, and is issued by the DODAG root to construct a new DAG and then sent in multicast through the DODAG structure. The DIO message carries relevant network information that allows a node to discover a RPL instance, learn its configuration parameters, select a DODAG parent set, and maintain the DODAG. The format of the DIO Base Object is presented in Fig. 2.8. The main DIO Base Object fields are: (i) RPLInstanceID, is an 8 bit information initiated by the DODAG root that indicates the ID of the RPL instance that the DODAG is part of, (ii) Version Number, indicates the version number of a DODAG that is typically incremented upon each network information update, and helps maintaining all nodes synchronized with new updates, (iii) Rank, a 16 bit field that specifies the rank of the node sending the DIO message, (vi) Destination Advertisement Trigger Sequence Number (DTSN) is an 8 bit flag that is used to maintain downward routes, (v) Grounded (G) is a flag indicating whether the current DODAG satisfies the application-defined objective, (vi) Mode of Operation (MOP) identifies the mode of operation of the RPL instance set by the DODAG root. Four operation modes have been defined and differ in terms of whether they support downward routes maintenance and multicast or not. Upward routes are supported by default. Any node joining the DODAG must be able to cope with the MOP to participate as a router, otherwise it will be admitted as a leaf node, (vii) DODAGPreference (Prf) is a 3 bit field that specifies the preference degree of the current DODAG root as compared to other DODAG roots. It ranges from 0x00 (default value) for the least preferred degree, to 0x07 for the most preferred degree, (viii) DODAGID is a 128 bit IPv6 address set by a DODAG root, which uniquely identifies a DODAG. Finally, DIO Base Object may also contain an Option field.
The Android OS has four main paradigms . The first one is related with the whole Android world and it must be Open Source. The second regards the creation of new applications and all of them must be created equal. The third paradigm is the applications boundaries. These applications must be rich and innovative supporting all kinds of information provided by Web services, other phones or even ubiquitous systems. The last one reflects the speed of the application development and deploying. Based on Linux Kernel, Android was built from scratch in order to allow developers to create applications that take full advantage of all characteristics of the handset. For example, an application can call upon any core phone functionality such as making calls, text messaging or using the camera. Through this characteristic the developers can aim to better, cohesive and rich applications. The authors had used this characteristic to operate the telephony functionality and invoke a call in an emergency scenario. Using the Linux Kernel as its foundation, Android is capable of adapting to any new emergent technology as soon it goes out, plus it can have millions of people working to improve base functionalities.