In this paper, we propose a new routing protocol for heterogeneous Wireless Body Area Sensor Networks (WBASNs); Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficient Multi-hop ProTocol (M-ATTEMPT). A prototype is defined for employing heterogeneous sensors on human body. Direct communication is used for real-time traffic (critical data) or on-demand data while Multi-hop communication is used for normal data delivery. One of the prime challenges in WBASNs is sensing of the heat generated by the implanted sensor nodes. The proposed routing algorithm is thermal-aware which senses the link Hot-spot and routes the data away from these links. Continuous mobility of human body causes disconnection between previous established links. So, mobility support and energy-management is introduced to overcome the problem. Linear Programming (LP) model for maximum information extraction and minimum energy consumption is presented in this study. MATLAB simulations of proposed routing algorithm are performed for lifetime and successful packet delivery in comparison with Multi-hop communication. The results show that the proposed routing algorithm has less energy consumption and more reliable as compared to Multi-hop communication.

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Modern health care system is one of the most popular Wireless Body Area Sensor Network (WBASN) applications and a hot area of research subject to present work. In this paper, we present Reliability Enhanced-Adaptive Threshold based Thermalunaware Energy-efficient Multi-hop ProTocol (RE-ATTEMPT) for WBASNs. The proposed routing protocol uses fixed deployment of wireless sensors (nodes) such that these are placed according to energy levels. Moreover, we use direct communication for the delivery of emergency data and multihop communication for the delivery of normal data. RE-ATTEMPT selects route with minimum hop count to deliver data which downplays the delay factor. Furthermore, we conduct a comprehensive analysis supported by MATLAB simulations to provide an estimation of path loss, and problem formulation with its solution via linear programming model for network lifetime maximization is also provided. In simulations, we analyze our protocol in terms of network lifetime, packet drops, and throughput. Results show better performance for the proposed protocol as compared to the existing one.

Wireless Sensor Networks (WSNs) are expected to find wide applicability and increasing deployment in near future. In this paper, we propose a new protocol, Threshold Sensitive Stable Election Protocol (TSEP), which is reactive protocol using three levels of heterogeneity. Reactive networks, as opposed to proactive networks, respond immediately to changes in relevant parameters of interest. We evaluate performance of our protocol for a simple temperature sensing application and compare results of protocol with some other protocols LEACH, DEEC, SEP, ESEP and TEEN. And from simulation results it is observed that protocol outperforms concerning life time of sensing nodes used.

We propose forwarding-function ( ) based routing protocol for underwater sensor networks (UWSNs): improved adaptive mobility of courier nodes in threshold-optimized depth-based-routing (iAMCTD). Unlike existing depth-based acoustic protocols, the proposed protocol exploits network density for time-critical applications. In order to tackle flooding, path loss, and propagation latency, we calculate optimal holding time ( ) and use routing metrics: localization-free signal-to-noise ratio (LSNR), signal quality index (SQI), energy cost function (ECF), and depth-dependent function (DDF). Our proposal provides on-demand routing by formulating hard threshold ( th ), soft threshold ( th ), and prime energy limit ( prime ). Simulation results verify effectiveness and efficiency of the proposed iAMCTD. BackgroundUnderwater acoustic sensor networks (UASNs), as a subclass of wireless sensor networks (WSNs), are specifically used for monitoring purposes in aqueous environment. The acoustic wireless sensors along with sink(s), distributed under water, constitute the basic body of UASN, where acoustic sensors gather the information of interest and then following a routing strategy forward these data to the end station. WHOI Micro-Modem [1] and Crossbow Mica2 [2] are among the commercially available sensors for underwater environments. Sink is generally supposed to have no power constraint, whereas the acoustic sensors are equipped with limited battery power. These networks provide diversified range of applications like pollution monitoring, ocean current detection, submarine discovery, deep sea explorations, and seabed management.Due to the nature of aqueous environment, improving energy efficiency at routing layer is a challenging task. Moreover, as there are major differences between terrestrial and underwater conditions, hence the basic concepts of terrestrial routing can not be implemented in UWSNs. To tackle these problems, researchers exercise the role of low speed acoustic signals for aqueous communication and sea navigation systems, leading to high propagation delay and transmission losses. High shipping activity, thermal noise, and turbulent noise also increase the error rate. Authors in [3] design the underwater acoustic channel to descriptively analyze the total noise density and path loss. On the other hand [4], it investigates diverse routing architectures for 2-dimensional and 3-dimensional UWSNs. Fundamental analyses of aqueous conditions show that reactive routing is more challenging than the proactive one. Battery replacement and efficient routing are among the solutions to overcome the

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Sensor networks feature low-cost sensor devices with wireless network capability, limited transmit power, resource constraints, and limited battery energy. Cooperative routing exploits the broadcast nature of wireless medium and transmits cooperatively using nearby sensor nodes as relays. It is a promising technique that utilizes cooperative communication to improve the communication quality of single-antenna sensor nodes. In this paper, we propose a cooperative transmission scheme for underwater sensor networks (UWSNs) to enhance the network performance. Cooperative diversity has been introduced to combat fading. Cooperative UWSN (Co-UWSN) is proposed, which is a reliable, energy-efficient, and high throughput routing protocol for UWSN. Destination and potential relays are selected that utilize distance and signal-to-noise ratio computation of the channel conditions as cost functions. This contributes to sufficient decrease in path losses occurring in the links and transferring of data with much reduced path loss. Simulation results show that Co-UWSN protocol performs better in terms of end-to-end delay, energy consumption, and network lifetime. Selected protocols for comparison are energy-efficient depth-based routing (EEDBR), improved adaptive mobility of courier nodes in threshold-optimized depth-based routing (iAMCTD), cooperative routing protocol for UWSN, and cooperative partner node selection criteria for cooperative routing Coop (Re and dth).

Abstract:The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR) with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm (CSA), which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart Electricity Storage System (ESS) is also taken into account for more efficient operation of the Home Energy Management System (HEMS). Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is implemented in a smart building; comprised of thirty smart homes (apartments), Real-Time Pricing (RTP) and Critical Peak Pricing (CPP) signals are examined in terms of electricity cost estimation for both a single smart home and a smart building. In addition, feasible regions are presented for single and multiple smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results demonstrate the effectiveness of our proposed scheme for single and multiple smart homes in terms of electricity cost and PAR minimization. Moreover, there exists a tradeoff between electricity cost and user waiting.