Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks

In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications

Modern Clustering Techniques in Wireless Sensor Networks

Wireless sensor networks (WSNs) are employed in various applications from healthcare to military. Due to their limited, tiny power sources, energy becomes the most precious resource for sensor nodes in such networks. To optimize the usage of energy resources, researchers have proposed several ideas from diversified angles. Clustering of nodes plays an important role in conserving energy of WSNs. Clustering approaches focus on resolving the conflicts arising in effective data transmission. In this chapter, we have outlined a few modern energy-efficient clustering approaches to improve the lifetime of WSNs. The proposed clustering methods are: (i) fuzzy-logic-based cluster head election, (ii) efficient sleep duty cycle for sensor nodes, (iii) hierarchical clustering, and (iv) estimated energy harvesting. Classical clustering approaches such as low energy adaptive clustering hierarchy (LEACH) and selected contemporary clustering methods are considered for comparing the performance of proposed approaches. The proposed modern clustering approaches exhibit better lifetime compared to the selected benchmarked protocols

Solutions and Recent Challenges Related to Energy in Wireless Body Area Networks with Integrated Technologies: Applications and Perspectives

في هذه الورقة، بحثنا في بعض أحدث بروتوكولات التوجيه الموفرة للطاقة لشبكات منطقة الجسم اللاسلكية. شهدت هذه التكنولوجيا تطورات في الآونة الأخيرة حيث يتم حقن أجهزة استشعار لاسلكية في جسم الإنسان لاستشعار وقياس معايير الجسم مثل درجة الحرارة ونبض القلب ومستوى الجلوكوز. تقوم هذه المستشعرات اللاسلكية الدقيقة بجمع معلومات بيانات الجسم وإرسالها عبر شبكة لاسلكية وإلى المحطة الأساسية. يتم فحص قياسات البيانات من قبل الطبيب أو الطبيب ويقترح العلاج المناسب. يتم إجراء الاتصال بالكامل من خلال بروتوكولات التوجيه في بيئة الشبكة. يستهلك بروتوكول التوجيه الطاقة أثناء المساعدة في الاتصال دون توقف في البيئة اللاسلكية. بسبب الحجم الصغير جدًا ، فإن استهلاك الطاقة مهم جدًا. لقد ركزنا على البروتوكولات التي توفر كفاءة استخدام الطاقة وتحسين عمر الشبكة، والإنتاجية، وفقدان الحد الأدنى من المسار. سنناقش بعض أحدث بروتوكولات التوجيه الموفرة للطاقة في هذه الورقة، في وقت لاحق يتم تقديم مقارنة مع جدول مناسب. بالإضافة إلى ذلك، تمت مناقشة التحديات الأخيرة والتطبيق المحتمل ووجهات النظر.          In this paper, we have investigated some of the most recent energy efficient routing protocols for wireless body area networks. This technology has seen advancements in recent times where wireless sensors are injected in the human body to sense and measure body parameters like temperature, heartbeat and glucose level. These tiny wireless sensors gather body data information and send it over a wireless network to the base station. The data measurements are examined by the doctor or   physician and the suitable cure is suggested. The whole communication is done through routing protocols in a network environment. Routing protocol consumes energy while helping non-stop communication in a wireless environment. Because of the very tiny size, energy consumption matters a lot. We have focused on the protocols, which provide energy efficiency and improve network lifetime, through put and minimal path loss. We will be discussing some of the most recent energy efficient routing protocols in this paper; later their comparison with an appropriate table is presented. In addition, recent challenges, possible application and perspectives are discussed.  &nbsp

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out

Energy Efficient Cluster Based Routing Protocol for Dynamic and Static Nodes in Wireless Sensor Network

Power consumption is considered one of the most significant challenges in the wireless network sensors (WSNs). In this paper, an investigation of the power consumption is done by making a comparison between static and dynamic WSNs. We have compared the results of the static network with the results of the dynamic network. Static and dynamic wireless Sensor networks have the same architecture (Homogenous) and proposed protocol. Depending on the suggested protocol, the simulation results show that the energy consumption in the static wireless sensor network was less than the dynamic wireless sensor network. However, moving the sensors in the dynamic WSN present real improvement in delivering packets to the base station. In the proposed routing protocol, transmitting data process is done in a hierarchal way. Cheap sensors are introduced and deploy them intensively to improve the QoS in the network. The final results and the conclusion are reported

Unified Role Assignment Framework For Wireless Sensor Networks

Wireless sensor networks are made possible by the continuing improvements in embedded sensor, VLSI, and wireless radio technologies. Currently, one of the important challenges in sensor networks is the design of a systematic network management framework that allows localized and collaborative resource control uniformly across all application services such as sensing, monitoring, tracking, data aggregation, and routing. The research in wireless sensor networks is currently oriented toward a cross-layer network abstraction that supports appropriate fine or course grained resource controls for energy efficiency. In that regard, we have designed a unified role-based service paradigm for wireless sensor networks. We pursue this by first developing a Role-based Hierarchical Self-Organization (RBSHO) protocol that organizes a connected dominating set (CDS) of nodes called dominators. This is done by hierarchically selecting nodes that possess cumulatively high energy, connectivity, and sensing capabilities in their local neighborhood. The RBHSO protocol then assigns specific tasks such as sensing, coordination, and routing to appropriate dominators that end up playing a certain role in the network. Roles, though abstract and implicit, expose role-specific resource controls by way of role assignment and scheduling. Based on this concept, we have designed a Unified Role-Assignment Framework (URAF) to model application services as roles played by local in-network sensor nodes with sensor capabilities used as rules for role identification. The URAF abstracts domain specific role attributes by three models: the role energy model, the role execution time model, and the role service utility model. The framework then generalizes resource management for services by providing abstractions for controlling the composition of a service in terms of roles, its assignment, reassignment, and scheduling. To the best of our knowledge, a generic role-based framework that provides a simple and unified network management solution for wireless sensor networks has not been proposed previously

E2BNAR: Energy Efficient Backup Node Assisted Routing for Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), each sensor node can only use so much power before recharging. If energy is depleted too quickly, nodes will fail one by one, bringing down the network as a whole. To this end, a design is needed to reduce the burden on the sensor nodes' power supplies while extending the network's useful life. This paper proposes a new approach, called Energy Efficient Backup Node Assisted Routing, to accomplish this (E2BNAR). Each primary node in the network has a group of backup nodes to ensure the network continues functioning. Assuming that the sensor nodes are capable of energy harvesting, E2BNAR finds the best backup node by analyzing the statistical relationship between energy harvesting and consumption rates. Periodically, residual energy is used to analyze the current energy consumption rate. When evaluating performance, several different indicators are taken into account. These include the Packet Delivery Ratio, Throughput, Average Energy Consumption, and Number of Awakened Sensor Nodes. Through analysis and experimentation in several settings, the proposed method's efficacy has been established