Framework for Cross Layer Energy Optimization in Wireless Sensor Networks

Cross-layer routing technique interacts among the various layers of the OSI model and exchanges information among them. It enhances the usage of network resources and achieves significant performance improvements in Quality of Service (QoS) parameters. The Low Energy Adaptive Clustering Hierarchy Protocol (LEACH) routing algorithm consumes higher energy due to communication overhead and thus, a hierarchical model-based routing protocol named Cross-Layer Energy Efficient Scalable-Low Energy Adaptive Clustering Hierarchy Protocol (CLEES-LEACH) is proposed. This increases scalability using the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol between the intermediary node and cluster head, with the overhead of latency. A Linear Programming model is used, which further makes use of scheduling to overcome latency. Energy efficiency and latency are addressed with the proposed cross-layer routing algorithm CLEESLEACH. The cross-layer design establishes Physical, Media Access Control (MAC), and Network layer interactions in the proposed algorithm. The present LEACH algorithm also increases the network overhead as there is no mechanism for communication among the network layer and consumes high energy. In the proposed algorithm CLEES-LEACH, latency is reduced to 25% and throughput is maximized to 20% compared to existing Energy-Efficient Distributed Schedule Based protocol (EEDS) and Integer Linear Programming (ILP) protocols. The energy consumption is also reduced to 20 % and the scalability is increased to 10 % compared to the existing LEACH and CL-LEACH

Cluster Based Algorithm for Energy Conservation and Lifetime Maximization in Wireless Sensor Networks

One of the most critical issues in designing Wireless Sensor Network (WSN) is to minimize the energy consumption. In Wireless Sensor Networks, data aggregation reduces the redundancy among sensed data and optimal sensor routing algorithm provides strategy for data gathering with minimum energy. The energy consumption is reduced by combining data fusion and cluster based routing. In this paper, we propose a K-means Fusion Steiner Tree (KFST) for energy efficient data gathering in sensor networks, which optimizes data transmission cost and the data fusion cost. This cost reduction increases the lifetime of a Sensor Network. The result of the proposed protocol KFST is compared with Adaptive Fusion Steiner Tree (AFST) and KFST produces better result than the existing protocols

Multiple dynamic sinks to maximize the lifetime and conservation of energy in wireless sensor networks

Wireless sensor networks (WSNs) consist of battery operated tiny sensor nodes and connected in a network for communication. Improving the lifetime of sensor network and energy conservation are the critical issues in WSNs. Nodes closer to the sink node drains their energy faster due to continuous and larger transmission of data towards a sink node. Dynamic Sinks solve the problem of lifetime and energy in WSNs. It moves dynamically to particular positions among the different positions in a predetermined order to collect data from sensor nodes. There is a considerable delay in the case of single mobile sink. In this paper we use the concept of multiple Dynamic sinks to collect data in different zones which in turn coordinate to consolidate the data and complete the process of receiving data from all the sensor nodes. A distributed algorithm synchronizes all dynamic sinks and it is used to reduce delay in consolidation of data and reduces the overall energy consumption. This twin gain increases the lifetime of wireless sensor network and it reduces delay. Simulation results using multiple dynamic synchronized Sinks clearly show that there is an improvement of the lifetime and energy conservation of wireless sensor networks in comparison with single mobile sink and static sink

CEAR: Cluster based Energy Aware Routing Algorithm to Maximize Lifetime of Wireless Sensor Networks (WSNs)

Technological development in wireless communication enables the development of smart, tiny, low cost and low power sensor nodes to outperform for various applications in Wireless Sensor Networks. In the existing Tabu search algorithm, clusters are formed using initial solution algorithm to conserve energy. We propose a Cluster Based Energy Aware Routing (CEAR) algorithm to maximize energy conservation and lifetime of network with active and sleep nodes. The proposed algorithm, removes duplication of data through aggregation at the cluster heads with active and sleep modes. A comparative study of CEAR algorithm with Tabu search algorithm is obtained. Comparative study shows improvement in the Lifetime and energy conservation by 17 and 22 % respectively over the existing algorithm

SEAD: source encrypted authentic data for wireless sensor networks

One of the critical issues in WSNs is providing security for the secret data in military applications. It is necessary to ensure data integrity and authentication for the source data and secure end-to-end path for data transmission. Mobile sinks are suitable for data collection and localization. Mobile sinks and sensor nodes communicate with each other using their public identity, which is prone to security attacks like sink replication and node replication attack. In this work, we have proposed Source Encrypted Authentic Data algorithm (SEAD) that hides the location of mobile sink from malicious nodes. The sensed data is encrypted utilizing symmetric encryption---Advanced Encryption Standards (AES) and tracks the location of the mobile sink. When data encounters a malicious node in a path, then data transmission path is diverted through a secure path. SEAD uses public encryption---Elliptic Curve Cryptography (ECC) to verify the authenticity of the data. Simulation results show that the proposed algorithm ensures data integrity and node authenticity against malicious nodes. Double encryption in the proposed algorithm produces better results in comparison with the existing algorithms

Bayesian Estimation Model for Trust dependent Greedy Antivoid Routing (TGAR) in Wireless Sensor Networks (WSNs)

Wireless Sensor Networks consist of tiny battery operated sensor nodes and which are connected in a network for communication. Energy, lifetime and reliable data delivery are the major issues in Wireless Sensor Networks (WSNs). The objective of any routing algorithm in WSN is successful data delivery. The existing Greedy Antivoid Routing (GAR) uses the Rolling ball Un-directed Traversal, to guarantee the packet delivery from source to destination. In the case of sparse network, when it experiences either an obstacle or void in the route, then it fails to deliver the data. To address these issues, we propose Trust dependent Greedy Antivoid Routing (TGAR) algorithm to find reliable path from the source to the sink. We use Bayesian estimation model to calculate the trust value for each path. Based on the trust value path is selected for the transmission of data. Simulation results show that TGAR achieves successful data delivery, higher throughput and lifetime with minimum energy consumption than the existing Greedy Antivoid Routing (GAR) Algorithm

ATMC: Anonymity and Trust Management Scheme Applied to Clustered Wireless Sensor Networks

Wireless Sensor Networks consists of sensor nodes that are capable of sensing the information and maintaining security. In this paper, an Anonymity and Trust Management Scheme applied to Clustered Wireless Sensor Networks (ATMC) is proposed which enhances the security level. It also provides a stable path for communication. It is observed that the performance of the network is better than existing schemes through simulation.[PUBLICATION ABSTRACT

Multiple mobile synchronised sinks (MMSS) for energy efficiency and lifetime maximization in wireless sensor networks

Wireless Sensor Networks(WSNs) consist of battery operated sensor nodes. Improving the lifetime of sensor network is a critical issue. Nodes closer to the sink node drains energy faster due to large data transmission towards a sink node. This problem is resolved through mobility of the sink node. The Mobile sink moves to particular positions in predetermined order to collect data from the sensor nodes. There is considerable delay in the case of single mobile sink. In this paper we have used the concept of multiple mobile sinks to collect data in different zones which in turn coordinate to consolidate the data and complete the processing of data received from all the sensor nodes. A distributed algorithm synchronizing all the mobile sinks are used to reduce the delay in consolidation of data and reducing the overall energy consumption. The twin gain increases the lifetime of the Wireless Sensor Network. Simulation results using Multiple Mobile Synchronized Sinks clearly shows that there is an increase of 28 and 56 in the lifetime of the Wireless Sensor Networks in comparison with Single Mobile Sink and Static Sink respectively

TGAR: Trust Dependent Greedy Anti-void Routing in Wireless Sensor Networks (WSNs)

In Wireless Sensor Networks (WSNs), energy and reliable data delivery are two major issues. Sending data from source to destination without void problem is an objective of any routing algorithm. The existing Greedy Anti-void Routing (GAR) uses the Rolling ball Undirected Traversal to guarantee the packet delivery from source to the destination. In the case of sparse network when it encounters an obstacle in the route it fails to deliver the data. To address this issue, we propose Trust dependent Greedy Anti-void Routing (TGAR) to find the reliable path from source to sink. We use Bayesian estimation model to calculate the trust value for the entire path. Simulation results show that TGAR achieves successful data delivery and energy conservation in sparse networks when compared with the existing Greedy Anti-void Routing (GAR) Algorithm. © 2013 Springer Science+Business Media New York