608 research outputs found
Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques
A wide range of academic scholars, engineers, scientific and technology communities are interested in energy utilization of Wireless Sensor Networks (WSNs). Their extensive research is going on in areas like scalability, coverage, energy efficiency, data communication, connection, load balancing, security, reliability and network lifespan. Individual researchers are searching for affordable methods to enhance the solutions to existing problems that show unique techniques, protocols, concepts, and algorithms in the wanted domain. Review studies typically offer complete, simple access or a solution to these problems. Taking into account this motivating factor and the effect of clustering on the decline of energy, this article focuses on clustering techniques using various wireless sensor networks aspects. The important contribution of this paper is to give a succinct overview of clustering
QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK
A Wireless Sensor Networks (WSN) is composed of a large number of low-powered
sensor nodes that are randomly deployed to collect environmental data. In a WSN,
because of energy scarceness, energy efficient gathering of sensed information is one
of the most critical issues. Thus, most of the WSN routing protocols found in the
literature have considered energy awareness as a key design issue. Factors like
throughput, latency and delay are not considered as critical issues in these protocols.
However, emerging WSN applications that involve multimedia and imagining sensors
require end-to-end delay within acceptable limits. Hence, in addition to energy
efficiency, the parameters (delay, packet loss ratio, throughput and coverage) have
now become issues of primary concern. Such performance metrics are usually
referred to as the Quality of Service (QoS) in communication systems. Therefore, to
have efficient use of a sensor node’s energy, and the ability to transmit the imaging
and multimedia data in a timely manner, requires both a QoS based and energy
efficient routing protocol. In this research work, a QoS based energy efficient routing
protocol for WSN is proposed. To achieve QoS based energy efficient routing, three
protocols are proposed, namely the QoS based Energy Efficient Clustering (QoSEC)
for a WSN, the QoS based Energy Efficient Sleep/Wake Scheduling (QoSES) for a
WSN, and the QoS based Energy Efficient Mobile Sink (QoSEM) based Routing for a
Clustered WSN.
Firstly, in the QoSEC, to achieve energy efficiency and to prolong
network/coverage lifetime, some nodes with additional energy resources, termed as
super-nodes, in addition to normal capability nodes, are deployed. Multi-hierarchy
clustering is done by having super-nodes (acting as a local sink) at the top tier, cluster
head (normal node) at the middle tier, and cluster member (normal node) at the lowest
tier in the hierarchy. Clustering within normal sensor nodes is done by optimizing the
network/coverage lifetime through a cluster-head-selection algorithm and a
sleep/wake scheduling algorithm. QoSEC resolves the hot spot problem and prolongs
network/coverage lifetime.
Secondly, the QoSES addressed the delay-minimization problem in sleep/wake
scheduling for event-driven sensor networks for delay-sensitive applications. For this
purpose, QoSES assigns different sleep/wake intervals (longer wake interval) to
potential overloaded nodes, according to their varied traffic load requirement defined
a) by node position in the network, b) by node topological importance, and c) by
handling burst traffic in the proximity of the event occurrence node. Using these
heuristics, QoSES minimizes the congestion at nodes having heavy traffic loads and
ultimately reduces end-to-end delay while maximizing the throughput.
Lastly, the QoSEM addresses hot spot problem, delay minimization, and QoS
assurance. To address hot-spot problem, mobile sink is used, that move in the network
to gather data by virtue of which nodes near to the mobile sink changes with each
movement, consequently hot spot problem is minimized. To achieve delay
minimization, static sink is used in addition to the mobile sink. Delay sensitive data is
forwarded to the static sink, while the delay tolerant data is sent through the mobile
sink. For QoS assurance, incoming traffic is divided into different traffic classes and
each traffic class is assigned different priority based on their QoS requirement
(bandwidth, delay) determine by its message type and content. Furthermore, to
minimize delay in mobile sink data gathering, the mobile sink is moved throughout
the network based on the priority messages at the nodes. Using these heuristics,
QoSEM incur less end-to-end delay, is energy efficient, as well as being able to
ensure QoS.
Simulations are carried out to evaluate the performance of the proposed protocols
of QoSEC, QoSES and QoSEM, by comparing their performance with the established
contemporary protocols. Simulation results have demonstrated that when compared
with contemporary protocols, each of the proposed protocol significantly prolong the
network and coverage lifetime, as well as improve the other QoS routing parameters,
such as delay, packet loss ratio, and throughput
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
On demand multicast routing in wireless sensor networks
The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs
On demand multicast routing in wireless sensor networks
The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs
Metaheuristics Techniques for Cluster Head Selection in WSN: A Survey
In recent years, Wireless sensor communication is growing expeditiously on the capability to gather information, communicate and transmit data effectively. Clustering is the main objective of improving the network lifespan in Wireless sensor network. It includes selecting the cluster head for each cluster in addition to grouping the nodes into clusters. The cluster head gathers data from the normal nodes in the cluster, and the gathered information is then transmitted to the base station. However, there are many reasons in effect opposing unsteady cluster head selection and dead nodes. The technique for selecting a cluster head takes into factors to consider including residual energy, neighbors’ nodes, and the distance between the base station to the regular nodes. In this study, we thoroughly investigated by number of methods of selecting a cluster head and constructing a cluster. Additionally, a quick performance assessment of the techniques' performance is given together with the methods' criteria, advantages, and future directions
UHEED - an unequal clustering algorithm for wireless sensor networks
Prolonging the lifetime of wireless sensor networks has always been a determining factor when designing and deploying such networks. Clustering is one technique that can be used to extend the lifetime of sensor networks
by grouping sensors together. However, there exists the hot spot problem which causes an unbalanced energy consumption in equally formed clusters. In this paper, we propose UHEED, an unequal clustering algorithm which mitigates this problem and which leads to a more uniform residual energy in the network and improves the network lifetime. Furthermore, from the simulation results presented, we were able to deduce the most appropriate unequal cluster size to be used
- …