Enhanced Metaheuristics-Based Clustering Scheme for Wireless Multimedia Sensor Networks

Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended user.With the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target domain.The existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia content.Since energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network lifetime.With this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for WMSN.The proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum computing.The proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance measures.The simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.

Energy Efficient and QoS Aware Framework for Video Transmission over Wireless Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs), is a network of sensors, which are limited in terms of memory, computing, bandwidth, and battery lifetime. Multimedia transmission over WSN requires certain QoS guarantees such as huge amount of bandwidth, strict delay and lower loss ratio that makes transmitting multimedia is a complicated task. However, adopting cross-layer approach in WMSNs improves quality of service of WSN under different environmental conditions. In this work, an energy efficient and QoS aware framework for transmitting multimedia content over WSN (EQWSN) is presented, where packet, queue and path scheduling were introduced. It adapts the application layer parameter of video encoder to current wireless channel state, and drops less important packets in case of network congestion according to packet type. Finally, the path scheduling differentiates packets types/priority and route them through different paths with different QoS considering network lifetime. Simulation results show that the new scheme EQWSN transmits video quality with QoS guarantees in addition to prolonging network lifetime.

Node correlation clustering algorithm for wireless multimedia sensor networks based on overlapped FoVs

In this paper, a clustering algorithm is proposed based on the high correlation among the overlapped field of views for the wireless multimedia sensor networks. Firstly, by calculating the area of the overlapped field of views （FoVs） based on the gird method, node correlations have been obtained. Then, the algorithm utilizes the node correlations to partition the network region in which there are high correlation multimedia sensor nodes. Meanwhile, in order to minimize the energy consumption for transmitting images, the strategy of the cluster heads election is proposed based on the cost estimation, which consists of signal strength and residual energy as well as the node correlation. Simulation results show that the proposed algorithm can balance the energy consumption and extend the network lifetime effectively.

Novel congestion control approach in wireless multimedia sensor networks

Data generated in wireless multimedia sensor networks （WMSNs） may have different importance and it has been claimed that the network exert more efforts in servicing applications carrying more important information. Nevertheless, importance of packets cannot generally be accurately represented by a static priority value. This article presents a dynamic priority based congestion control （DPCC） approach that makes two major innovations in WMSNs. First, DPCC employs dynamic priority to represent packet importance. Second, it prioritizes the local traffic of motes near the base station when WMSN is highly congested. Simulation results confirm the superior performance of the proposed approach with respect to energy efficiency, loss probability and latency as well.

Multi-level cross-layer protocol for end-to-end delay provisioning in wireless multimedia sensor networks

Rapid developments in information and communication technology in recent years have posed a significant challenge in wireless multimedia sensor networks(WMSNs).End-to-end delay and reliability are the critical issues in multimedia applications of sensor networks.In this paper we provide a new cross-layer approach for provisioning the end-to-end delay of the network at a desirable level of the packet delivery ratio(PDR),used here as a measure of network reliability.In the proposed multi-level cross-layer(MLCL)protocol,the number of hops away from the sink is used to set a level for each node.A packet is routed through the path with the minimum hop count to the sink using this level setting.The proposed protocol uses cross-layer properties between the network and medium access control(MAC)layers to estimate the minimum delay,with which a node can deliver a packet to the sink.When a node wants to send a packet,the MLCL protocol compares this minimum delay with the time to live(TTL)of a packet.If the TTL of the packet is higher than the minimum delay,the node sends the packet through the path with the minimum delay;otherwise,the node drops the packet as the node cannot deliver it to the sink within the TTL duration.This packet dropping improves network performance because the node can send a useful packet instead of an unusable packet.The results show a superior performance in terms of end-to-end delay and reliability for the proposed protocol compared to state-of-the-art protocols.

Image compression scheme based on PCA for wireless multimedia sensor networks

In combination of the characteristic of the network architecture of wireless multimedia sensor networks （WMSNs）, a distributed multi-node cooperative network （DMCN） model is designed by using the concept of in-network processing to improve their energy, memory and computational power. To balance the energy consumption of the network, according to roles division, camera nodes and common nodes are cooperated to accomplish the workload of image acquisition, compression and transmission. Camera nodes gather images and send blocking images to the common nodes in cluster. Common nodes adaptively compress the partitioned images by using a noise-tolerant distributed image compression （NDIC） algorithm based on principal component analysis （PCA） called NDIC-PCA algorithm and send the compressed data to the cluster head node. Then, the cluster head node sends the compressed image data to the station. Simulation results demonstrate that, DCNM can effectively balance the energy consumption of network and largely extend the network lifecycle. In addition, compared with previous algorithms, the proposed NDIC-PCA algorithm achieves higher peak signal to noise ratio without decreasing compression ratio.

Performance Improvement of Wireless Multimedia Sensor Networks Using MIMO and Compressive Sensing

Wireless Multimedia Sensor Networks(WMSN)are designed to transmit audio and video streams,still images,and scalar data.Multimedia transmission over wireless sensor networks has many applications,such as video surveillance,object tracking,telemedicine,theft control systems,and traffic monitoring.Researchers face many challenges,such as higher data rates,lower energy consumption,reliability,signal detection and estimation,uncertainty in network topology,quality of service(QoS),and security-and privacy-related issues to accomplish various applications of WMSN.This paper presents multiple input multiple output(MIMO)along with compressive sensing(CS)properties to improve system performance in terms of energy consumption and QoS in deep fade environments.The CS theory model has been proposed to reduce energy consumption by taking fewer measurements of the original signal or information and reconstructing it with acceptable image quality at the receiver side.The transmission and processing energy can be reduced by transmitting fewer measurements from the sensor side itself.The MIMO model and CS algorithm have been simulated,and results show that CS performs well on images.