Wireless Sensor Network

This work presents a healthcare monitoring system that can be used in an intensive care room. Biological information represented by ECG signals is achieved by ECG acquisition part . AD620 Instrumentation Amplifier selected due to its low current noise. The ECG signals of patients in the intensive care room are measured through wireless nodes. A base node is connected to the nursing room computer via a USB port , and is programmed with a specific firmware. The ECG signals are transferred wirelessly to the base node using nRF24L01+ wireless module. So, the nurse staff has a real time information for each patient available in the intensive care room. A star Wireless Sensor Network is designed for collecting ECG signals . ATmega328 MCU in the Arduino Uno board used for this purpose. Internet for things used For transferring ECG signals to the remote doctor, a Virtual Privet Network is established to connect the nursing room computer and the doctor computer . So, the patients information kept secure. Although the constructed network is tested for ECG monitoring, but it can be used to monitor any other signals.

payal_mahida@yahoo.co.in 1 , patelrahil43@yahoo.com 2 , patelparixit07@gmail.com 3 , modysnkt@gmail.com 4 Abstract: A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. The main goal of this paper is to analysis and Evaluation of AODV routing protocol for wireless sensor network and compares the Static and Dynamic Scenarios for PDR, e2e Delay and throughput. The goal of this work is to perform a simulation with different metrics, analysis of the results and deriving a conclusion on basis of performance evaluation.

Hierarchical routing performs energy-efficient routing in WSN, and contributes to overall system scalability and lifetime. In a hierarchical architecture, sensors organize themselves into clusters and each cluster has a cluster head, i.e. sensor nodes form clusters where the low energy nodes are used to perform the sensing in the proximity of the phenomenon. For the cluster based wireless sensor network, the cluster information and Cluster Head (CH) selection are the basic issues. The cluster head coordinates the communication among the cluster members and manages their data [11].

Abstract— A wireless sensor network (WSN) is energy con- strained, and the extension of its lifetime is one of the most important issues in its design. Usually, a WSN collects a large amount of data from the environment. In contrast to the conventional remote sensing – based on satellites that collect large images, sound files, or specific scientific data – sensor networks tend to generate a large amount of sequential small and tuple- oriented data from several nodes, which constitutes data streams. In this work, we propose and evaluate two algorithms based on data stream, which use sampling and sketch techniques, to reduce data traffic in a WSN and, consequently, decrease the delay and energy consumption. Specifically, the sampling solution, provides a sample of only log n items to represent the original data of n elements. Despite of the reduction, the sampling solution keeps a good data quality.

Wireless sensor network is an important technology that will change the world [11]. Wireless sensor networks consist of hundreds to thousands of low-power multifunctioning tiny sensor nodes which operate in an inaccessible environment, with limited computational and sensing capabilities. In recent developments the low-power wireless integrated micro sensor technologies have made these sensor nodes available in large numbers, at a low cost which is employed in the area of applications [2]. WSN is widely used in military and national security, environmental monitoring, home automation, traffic control, health application and many other fields. The main job of sensor network is to periodically collect data from area of interest and then sends back the data to the Base Station (BS) for analysis, which is usually located far from the target area [5]. The most restrictive factor in the life-time of wireless sensor network is limited energy resource of the sensor nodes. So energy consumption is main requirement in the design of sensor network protocols and algorithms. As the sensor nodes are equipped with small, limited power capacity batteries, the network should be energy efficient to increase the life span of the network [2,9]. Wireless sensor network design also demands requirements like fault tolerance, scalability, production costs, and reliability. So It is difficult that the designer takes consider these factors when designing protocols and algorithms in wireless sensor networks [2].

Abstract- Individual sensor nodes are low power devices which integrate computing, wireless communication and sensing capabilities to detect land mine. Such multiple nodes collectively form wireless sensor network. To detect landmine in ground surface, sensor node that able to sense the mine and to process the information locally are mounted on a mobile robot to scan the ground surface in the organized pattern resulting in detection of all the mines present in the proposed area which is synchronized by Infrared pills; the node can communicate to the data collection point (Sink) typically through wireless communication. The aggregation of such multitude of mobile nodes and a mobile sink forms a versatile mine detection unit. When the mine is detected the node routes it information to the hand held device (Base) through sink and stays in it position to help the demining crew to identify the position where the mine is present. When the demining crew presses a button the node continues in its pattern.

In wireless sensor 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.

Design requirements for security scheme include energy awareness, survivability and localization of attack impact given a highly vulnerable network that mainly operates unattended and scalability to a large dynamic network. One major challenge to dynamic keying schemes is the need for the participation (to varying degrees) of a key management authority (usually the base station) post network deployment. In this paper, we presented an energy efficient security scheme for wireless sensor network which provides an end-to-end and inter node authentication for all communication in an efficient manner. The design of the security scheme is motivated by the observation that different types of messages exchanged between sensor nodes have different security requirements and that a single keying mechanism is not suitable for meeting these different security requirements. Consequently our scheme includes support for establishing two types of keys per sensor node individual keys which are shared with the base station, pair wise keys shared with individual neighboring nodes in the network. A distinguishing feature of our scheme is that it restricts the security impact of a node compromise to the immediate network neighborhood of the compromised node. The key establishment and key updating procedures for a compromised is used by our scheme.

Abstract: It is important to increase the Wireless Sensor Network (WSN) lifetime, due to its limited energy resource, while meeting the constraints of applications. Recent Advances for In-Network Proc- essing (INP) motivate many WSN applications which are based on multi rate and distributed signal processing, and therefore require the support of rate-based routing as well as MAC and link layer de- signs to maximize the WSN lifetime. We propose a new scheme called “Rate Distribution (RateD)”, in which the application rate constraints are distributed in the WSN based on an optimized routing scheme. An optimal RateD was achieved by forming optimal data flows under rate constraints, which was an NP-complete problem. To reduce the complexity, a near optimization solution formed and ana- lyzed, and a practical rate-based routing selection based on rate assignment also proposed to achieve effective rate distributions. The simulation shows that this scheme significantly extends the WSN life- time for INP applications.

A wireless sensor network is a collection of sensor nodes which are deployed in a given area of interest[1]. A sensor node is made up of components such as sensing unit, processing unit, transceiver unit and a power unit. The sensor nodes collect the data from its neighbouring nodes and send the collected data to the neighbouring nodes that are situated in a single hop. Those nodes send in turn the collected data to the sink node. The sink node is responsible for collecting data from inside the network processing them and sending them to the outside world. The sensor nodes are equipped with battery and whose battery cannot be replaced after deployment, so the major concern is to conserve the energy of the sensor nodes. The nodes that are placed closer to the sink node have to do

B will quickly use up their batteries (because that these nodes near the sink needed to forward the packets sent from those nodes on the far side), and the wireless sensor network will be partitioned. Therefore, designing effective data collection architecture is an important research topic. Some researches [14]-[21] proposed constructing a collection architecture using a tree according to the mobility profile, which is generated according to the mobility model. Nevertheless, the actual object movement behavior may not match the mobility model and this difference may affect the performance of the collection architecture. Therefore, the Message-Tree Adaptive procedure (MTA) was proposed in [22] to dynamically adapt the object-tracking tree.

Energy constraint in wireless sensor network makes the challenges in query processing an important research area. We focus on application layer issues which contribute to the optimization of the query processing. We studied the performance of query processing engines (TinyDB, Cougar) from the perspective of location of metadata and query processing semantics. Centralized model of query processing can make accurate query plan but communication cost for metadata collection is bottleneck. Inter-WSN and intra- WSN partitioning of query with in-network processing of query processing operators along the minimum spanning tree routed at the sink node can reduce communication cost involved in metadata collection. We consider the case where queries are synchronously injected at the sink node and query is single long running aggregate query. In this paper, we address the problem of centralized metadata and formulate a solution based on distributed metadata. In the future we plan to extend our approach to support multiple query optimizations. Additionally, we plan to calculate of cost at different levels of wireless sensor network. This cost includes metadata collection, sampling cost, reporting cost and building structure cost.

In this work we present two contributions for the wireless sensor network (WSN) literature. The first one is a general model to achieve reproducibility in kernel level of parallel simulators. Unfortunately, users must implement how their simulations repeat from scratch in WSN sim- ulators, but a parallel or distributed simulation imposes the concurrence principle, not trivial to be implemented by non-specialists. Tests using the simulator named JSensor proved that the model guarantees the most restrict level of reproducibility, even when simulations adopt different number of threads or different machines in multiple runs. The second contribution is the JSensor simulator, a parallel general purpose simulator for large scale WSN applications and high-level distributed algorithms. JSensor introduces more realistic simulation elements, such as the environment represented by customizable cells and application-events representing natural phenomena, such as lightning, wind, sun, rain and more. The cells are placed in a grid that represents the environment with characteristics of the space defined by the users, such as temperature, pressure and air quality. Experimental evaluations show that JSensor has good scalability in multi-core computer architectures, achieving a speedup of 7.45 in a machine with 16 cores with Hyper-Threading Technology, thus 50% of cores are virtual ones. JSensor also proved to be 21% faster than OMNeT++ while simulating a flooding model.

The birth of wireless sensor network (WSN) has brought out the practical aspects of pervasive computing and networking. A wireless sensor network is a group of specialized sensor nodes each of which is small, lightweight and portable with a communication infrastructure intended to monitor and record conditions at diverse locations. Generally sensors are battery powered and have feeble data processing capability and short radio range [1]. The resource-constraint temperament of WSNs in terms of their size, cost, weight and lifetime [2] is a key area of apprehension for most applications using WSN. The best part of this resource constraint nature makes wireless sensor networks to be used in the context of high end applications, security applications and consumer applications [3]. The worst part of this calls for research on power limited capability thereby prolonging the network reliability and operation.

More closely related to this work are the intelligent sensors being developed and used by NASA in space technology [16]. In the domain of sensor system, many commercial sensors are available for measuring humidity [20]. These are highly accurate, but rather bulky and expensive, not targeted for low power WSN node. The intelligent humidity sensor presented in this paper, serves a different purpose. The aim of this system is to combine the features of sensor with processor to reduce the post processing overhead, thereby reducing the overall power consumption [23, 33]. These efforts have made available inexpensive intelligent sensors that are equipped with sensing, data processing and wireless communication capabilities for wireless sensor network node [29]. Realizing the full potential of the intelligent sensors will require a new approach to identify intelligent sensor applications to create the next-generation products and systems [34].

Vijay Chandrasekhar and Winston KG Seah et al. [10] surveyed the different localization schemes that can be used in underwater wireless sensor networks and the challenges in meeting those schemes. As underwater sensor networks use acoustic channels, so bandwidth limitation, propagation delay and bit error rate are main challenges. Most localization schemes require the location of some nodes in the network to be known in advance. These are called anchor nodes or reference nodes. Localization that uses reference nodes can be classified into two categories- first range based schemes that use range/bearing information, second range free schemes that do not use range/ bearing information. Range based schemes use one of time of arrival (ToA), time difference of arrival (TDoA), angle of arrival (AoA) for precise distance or angle measurement. Time synchronization and propagation delay are main challenges in range based scheme. Range free schemes do not use ToA, TDoA or AoA. Hop count based schemes and area based schemes are range free schemes. By comparison, range based schemes are used for fine grained location estimation while range free schemes only

Wireless Sensor Networks (WSN) are major research area in the past few decades. WSN is formed by collection of sensor nodes. Power source life and memory size limit the hardware sources and these will decide the lifesapn of sensor nodes in WSN. Therefore, many resources based research issues are evolved in WSN. This study focused security issue and proposed authentication system. As the sensor nodes are limited memory, the traditional authentication systems are uncomforted. Hence, secret handshake system using two authorities, namely Issue Authority and Validate Authority are proposed in this study. The proposed authentication system is called as, Secret Handshake Issue and Validate Authority (SHIVA). The proposed methodology is occupying lesser memory space and also reducing number of communication of sensor nodes for the authentication model. Therefore, the proposed methodology proved optimum for WSN.

The broadcast nature of wireless networks makes it a challenge to design MAC protocols for WSN 3 . For its simplicity and efficiency, collision-avoidance handshake is a widely used scheme in MACA to reduce the prevalent collision networks where the sender sends an RTS (request-to-send) and the receiver replies with CTS (clear-to-send). There may occur the problems of overhearing this communication signal like Hidden Node and Exposed Node problems which can be optimized using different variants of this protocol.

In this section, according to FlexiTP protocol, the corresponding routing tree is obtained. FlexiTP protocol includes two phases performed in each cluster. These two phases are the primary network operation and collecting the information. Collecting information is done through the tables which are divided between each branch nodes. In FlexiTP protocol, the collecting information phase is performed primarily and only in network operation. In the proposed protocol the buffers are used to repeat this phase several times. In following the buffers components will be described. On one hand, in this section we can use any other protocols for scheduling cluster nodes. On the other hand, the proposed protocol has a director and several head cluster, each of the clusters having one or more head cluster which are divided according to the their distance between several nodes. The chief director directs the head clusters.

Hardware complexity and power consumption are fundamental design criteria for portable communication devices of specific applications like sensor networks, smart cards etc. A stream cipher with modest hardware complexities has enormous significance in the design of stream cipher based cryptosystems. The main goal here is the process of generating the pseudo random bit string. Some of the known stream Ciphers are E0 used in Bluetooth, A5/1 used in GSM communications, RC4 and Grain in RFID applications.