Towards energy efficient clustering in wireless sensor networks: A comprehensive review

Clustering is one of the fundamental approaches used to optimize energy consumption in wireless sensor networks. Clustering protocols proposed in the literature can be classified according to different criteria related to their features such as the clustering methodology, objectives, cluster count and size, etc. This paper reviews the existing feature-based classifications of clustering protocols and elaborates a more generic and unified classification. It also analyzes and discusses the relevant design factors that may influence the energy efficiency of clustering protocols and accordingly proposes a new energy-oriented taxonomy. State-of-the-art clustering solutions are then reviewed and evaluated following the proposed taxonomy

Rate-distortion Balanced Data Compression for Wireless Sensor Networks

This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring spatio-temporal correlations among data samples. The adaptive rate-distortion feature balances the compressed data size (data rate) with the required error bound guarantee (distortion level). This compression relieves the strain on energy and bandwidth resources while collecting WSN data within tolerable error margins, thereby increasing the scale of WSNs. The algorithm is evaluated using real-world datasets and compared with conventional methods for temporal and spatial data compression. The experimental validation reveals that the proposed algorithm outperforms several existing WSN data compression methods in terms of compression efficiency and signal reconstruction. Moreover, an energy analysis shows that compressing the data can reduce the energy expenditure, and hence expand the service lifespan by several folds.Comment: arXiv admin note: text overlap with arXiv:1408.294

A Novel Routing Protocol For Wireless Sensor Networks With Improved Energy Efficient LEACH

Wireless Sensor Networks (Wsns) Have Been Widely Considered As One Of The Most Important Technologies For The Twenty-First Century. A Typical Wireless Sensor Network(WSN) Used For Environmental Condition Monitoring, Security Surveillance Of Battle-Fields, Wildlife Habitat Monitoring, Etc. Cluster-Based Hierarchical Routing Protocols Play An Essential Role In Decreasing The Energy Consumption Of Wireless Sensor Networks (Wsns). A Low-Energy Adaptive Clustering Hierarchy (LEACH) Has Been Proposed As An Application-Specific Protocol Architecture For Wsns. However, Without Considering The Distribution Of The Cluster Heads (Chs) In The Rotation Basis, The LEACH Protocol Will Increase The Energy Consumption Of The Network. To Improve The Energy Efficiency Of The WSN, We Propose A Novel Modified Routing Protocol In This Paper. The Newly Proposed Improved Energy-Efficient LEACH (IEE-LEACH) Protocol Considers The Residual Node Energy And The Average Energy Of The Networks. To Achieve Satisfactory Performance In Terms Of Reducing The Sensor Energy Consumption, The Proposed IEE-LEACH Accounts For The Numbers Of The Optimal Chs And Prohibits The Nodes That Are Closer To The Base Station (BS) To Join In The Cluster Formation. Furthermore, The Proposed IEE-LEACH Uses A New Threshold For Electing Chs Among The Sensor Nodes, And Employs Single Hop, Multi-Hop, And Hybrid Communications To Further Improve The Energy Efficiency Of The Networks. The Simulation Results Demonstrate That, Compared With Some Existing Routing Protocols, The Proposed Protocol Substantially Reduces The Energy Consumption Of Wsns

A Collective Adaptive Approach to Decentralised k-Coverage in Multi-robot Systems

We focus on the online multi-object k-coverage problem (OMOkC), where mobile robots are required to sense a mobile target from k diverse points of view, coordinating themselves in a scalable and possibly decentralised way. There is active research on OMOkC, particularly in the design of decentralised algorithms for solving it. We propose a new take on the issue: Rather than classically developing new algorithms, we apply a macro-level paradigm, called aggregate computing, specifically designed to directly program the global behaviour of a whole ensemble of devices at once. To understand the potential of the application of aggregate computing to OMOkC, we extend the Alchemist simulator (supporting aggregate computing natively) with a novel toolchain component supporting the simulation of mobile robots. This way, we build a software engineering toolchain comprising language and simulation tooling for addressing OMOkC. Finally, we exercise our approach and related toolchain by introducing new algorithms for OMOkC; we show that they can be expressed concisely, reuse existing software components and perform better than the current state-of-the-art in terms of coverage over time and number of objects covered overall

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Secured Clustering in Wireless Sensor Networks

Wireless sensor networks are being increasingly used in a wide variety of applications such as the environment, nuclear power plants, military and transportation, to name a few. These sensors are fragile devices, with minimal energy, storage and computational resources. The phenomenon that is sensed is relayed to a powerful base station for further analysis. A key issue in the design of communication protocols for wireless sensor networks is energy conservation. Another important criterion for sensor networks is security. This is particularly important in military applications and national infrastructure such as power plants and transportation systems. As far as we are aware, no protocols have been proposed for energy efficient secure communications. In previous work both security and energy efficiency have been considered separately in the design of protocols for sensor networks. In this thesis we propose a secure energy efficient communication protocol for wireless sensor networks. A clustered protocol based on "A key-management scheme for distributed sensor networks" proposed by V.D. Gligor is developed and simulated in this thesis. To further improve energy efficiency we apply the concept of a force to improve the coverage of the sensor nodes. The properties of our proposed algorithm have been analyzed. We propose in this thesis a secure scheme with clustering, a balanced secure scheme with clustering and finally a balanced clustered secure scheme after the application of force. Results show that the proposed balanced clustered secure scheme after the application of force provides the best energy efficiency as well as security. The secure scheme with no clustering gave the worst results.Computer Science Departmen

Equalized Cluster Head Election Routing Protocol for WSNs

In recent years, the growing interest in the WIRELESS SENSOR NETWORK (WISENET) is increases. Wireless Sensor Network is an emerging technology that promises a wide range of potential applications in both civilian and military areas. A sensor network consists of multiple detection stations called sensor nodes, each of which is small, lightweight and portable. Every sensor node is equipped with a Sensing Unit, Data Processing Unit, transceiver and power source. The development of WSNs largely depends on the availability of low-cost and low-power hardware and software platforms for sensor networks. Equalized Cluster Head Election Routing Protocol (ECHERP), pursues energy conservation through balanced clustering for Energy Efficiency