Distributed Power Allocation for Sink-Centric Clusters in Multiple Sink Wireless Sensor Networks

Due to the battery resource constraints, saving energy is a critical issue in wireless sensor networks, particularly in large sensor networks. One possible solution is to deploy multiple sink nodes simultaneously. Another possible solution is to employ an adaptive clustering hierarchy routing scheme. In this paper, we propose a multiple sink cluster wireless sensor networks scheme which combines the two solutions, and propose an efficient transmission power control scheme for a sink-centric cluster routing protocol in multiple sink wireless sensor networks, denoted as MSCWSNs-PC. It is a distributed, scalable, self-organizing, adaptive system, and the sensor nodes do not require knowledge of the global network and their location. All sinks effectively work out a representative view of a monitored region, after which power control is employed to optimize network topology. The simulations demonstrate the advantages of our new protocol

A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

A collaborative model for representing wireless sensor networks' entities and properties

Wireless sensor nodes are, typically, resource limited. Therefore, the major functions of the Wireless Sensor Network (WSN) cannot be accomplished without collaboration among sensor nodes. In this paper, we present the Wireless Sensor Networks Supported Cooperative Work (WSNSCW) model. The key contribution of this model, when comparing to other models, is allowing for the representation of all the components and properties of a WSN. We also present the main entities and properties of this graph-based model, as well as its formalization.info:eu-repo/semantics/publishedVersio

A review of routing protocols in wireless body area networks

Recent technological advancements in wireless communication, integrated circuits and Micro-Electro-Mechanical Systems (MEMs) has enabled miniaturized, low-power, intelligent, invasive/ non-invasive micro and nano-technology sensor nodes placed in or on the human body for use in monitoring body function and its immediate environment referred to as Body Area Networks (BANs). BANs face many stringent requirements in terms of delay, power, temperature and network lifetime which need to be taken into serious consideration in the design of different protocols. Since routing protocols play an important role in the overall system performance in terms of delay, power consumption, temperature and so on, a thorough study on existing routing protocols in BANs is necessary. Also, the specific challenges of BANs necessitates the design of new routing protocols specifically designed for BANs. This paper provides a survey of existing routing protocols mainly proposed for BANs. These protocols are further classified into five main categories namely, temperature based, cross-layer, cluster based, cost-effective and QoS-based routing, where each protocol is described under its specified category. Also, comparison among routing protocols in each category is given. © 2013 ACADEMY PUBLISHER

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio