Wireless Multimedia Sensor Networks(WMSNs) have the characteristics of limited resources, variable channel capacities and high data redundancy, which pose great challenges to the QoS routing of WMSNs. Addressing these issues, an Ant Colony Optimization-based Load Balancing Routing Algorithm (ACOLBR) is proposed. Firstly, the intra-cluster routing is built by the minimum spanning tree. And then the inter-cluster routing is built by the improved ant colony optimization algorithm to find an optimal path and some suboptimal paths. Simulation experiments demonstrate that ACOLBR has better scalability, adaptability, load balancing and end-to-end delay compared with AGRA and M-IAR. Therefore ACOLBR can effectively prolong the network lifetime and guarantee the QoS of data transmission.

An Ant Colony Optimization-based Load Balancing Routing Algorithm for Wireless Multimedia Sensor Networks

We optimize the cluster structure to solve problems such as the uneven energy consumption of the radar sensor nodes and random cluster head selection in the traditional clustering routing algorithm. According to the defined cost function for clusters, we present the clustering algorithm which is based on radio-free space path loss. In addition, we propose the energy and distance pheromones based on the residual energy and aggregation of the radar sensor nodes. According to bionic heuristic algorithm, a new ant colony-based clustering algorithm for radar sensor networks is also proposed. Simulation results show that this algorithm can get a better balance of the energy consumption and then remarkably prolong the lifetime of the radar sensor network.

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An energy consumption optimized clustering algorithm for radar sensor networks based on an ant colony algorithm

A Wireless Sensor Network (WSN) consists of large number of small, inexpensive nodes that depend on their sensors, transmission and routing capabilities to collect and disseminate critical data. The energy consumption is a key design criterion for WSN routing algorithms due to the limited availability of energy within network nodes. Hence, energy-efficient routing mechanism is one of the most critical issues in WSNs. In this paper a Biased Random Algorithm for Load Balancing (BRALB) in Wireless Sensor Networks for environment monitoring is proposed. It is based on energy biased random walk. It does not require any global information. It uses probability theory to acquire all the information it needs to route packets based on energy resources in each node. It is shown in this paper by using both simulation that BRALB uses the same energy as the shortest path first routing in cases where the message to be sent is comparatively small in size, with the inquiry message among the neighbors. It is also shown to balance the load (i.e. the packets to be sent) among the neighboring nodes.

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Biased random algorithm for load balancing in Wireless Sensor Networks (BRALB)

Wireless Sensor Networks(WSN) when sorted out as groups (clusters) increases throughput, energy savings and decreases delay. These types of WSN rely on cluster heads for data aggregation and transmission towards sink node. Subsequently cluster head nodes are outfitted with high energy. Conventional hierarchical routing protocols were not created considering security; they are helpless against Denial of Service (DoS) attacks. In the event that the information supply process is hampered and in this way the normal administrations get to be inaccessible because of the purposeful endeavors of the enemies, we consider this as a Denial of Service (DoS) attack. So in order to address this issue and to disseminate the computational heap of detection complexity among the cluster heads rather than the sink nodes, a distributed intrusion detection scheme (IDS) is developed. Among the various Denial of Service attacks, Flooding attacks consumes the maximum battery life of the sensor node, on the other hand Gray hole attack consumes the minimum battery life of the nodes. Thus based on energy these attacks are distinguished and isolated from the network using the proposed IDS and extensive simulations are carried out using NS2- MANNASIM framework.

Distributed detection of flooding and gray hole attacks in Wireless Sensor Network

Wireless Sensor Network has always captivated researchers to broaden up the field by critically evaluating and realizing its capabilities in various application areas Conceiving an idea of implementing wireless sensor network has shown many challenges ie node deployment, data clustering, data aggregation, energy efficiency, lifetime improvement, etc This paper deals with an important aspect ie clustering In this paper a new clustering approach has been proposed that combines the functionality of two popular approaches ie Voronoi diagrams and Ant Systems The simulations are performed in QualNet version 61 with IEEE 802154 at the MAC and Physical layers The proposed algorithm shows promising results as compare to that of AODV and OSPFv2 in terms of energy efficiency and overall performance

An Ant Voronoi Based Clustering Approach for Wireless Sensor Networks

Routing algorithms play important roles in wireless sensor networks (WSNs). Usually, nodes in a WSN run on battery with limited power. Hence, routing with efficient power consumption is becoming a critical issue for WSNs. In this paper, a routing algorithm, referred to as Energy Prediction and Ant Colony Optimization Routing (EPACOR), is proposed. In the EPACOR, when a node needs to deliver data to the sink, ant colony systems are used to establish the route with optimal or sub-optimal power consumption, and meanwhile, learning mechanism is embedded to predict the energy consumption of neighboring nodes when the node chooses a neighboring node added to the route. The EPACOR is compared both with the MST (Minimal Spanning Tree)-based routing algorithm following the Prim algorithm and with the Least Energy Tree (LET)-based routing algorithm following the Dijkstra algorithm. Numeric experiment shows that the EPACOR has the best network lifetime among the three while keeping energy consumption in low level.

Yi-ping Tang

Papers

An Ant Colony System Based Energy Prediction Routing Algorithms for Wireless Sensor Networks

Mathematical modeling method of competition window average length of IEEE 802.11 wireless network node