• Energy Research

In recent years, demand side management (DSM) techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart grid. In essence, five heuristic algorithms (the genetic algorithm (GA), the binary particle swarm optimization (BPSO) algorithm, the bacterial foraging optimization algorithm (BFOA), the wind-driven optimization (WDO) algorithm and our proposed hybrid genetic wind-driven (GWD) algorithm) are evaluated. These algorithms are used for scheduling residential loads between peak hours (PHs) and off-peak hours (OPHs) in a real-time pricing (RTP) environment while maximizing user comfort (UC) and minimizing both electricity cost and the peak to average ratio (PAR). Moreover, these algorithms are tested in two scenarios: (i) scheduling the load of a single home and (ii) scheduling the load of multiple homes. Simulation results show that our proposed hybrid GWD algorithm performs better than the other heuristic algorithms in terms of the selected performance metrics.

Après un développement réussi dans les services de santé, le WBASN est également utilisé dans d'autres domaines où une surveillance continue et à distance des soins de santé est nécessaire. Divers protocoles suggérés présentés dans la littérature pour améliorer les performances du WBASN en mettant l'accent sur le retard, l'efficacité énergétique et le routage. Dans cette recherche, nous nous concentrons sur l'augmentation de la période de stabilité et du débit, tout en diminuant de bout en bout. Deux nœuds de puits sont utilisés et le concept d'AnyCasting est introduit. Dans cette recherche, nous avons présenté un schéma AnyCasting In Dual Sink (ACIDS) pour WBASN et l'avons comparé aux protocoles existants LAEEBA et DARE. Les performances des ACIDES se sont avérées efficaces à 51 % et 13 % par rapport à LAEEBA et DARE respectivement en termes de débit. Les résultats montrent que, la période de stabilité des ACIDES est beaucoup plus grande que LAEEBA et OSE avec un minimum de retard. Le paramètre d'énergie dans LES ACIDES est en compromis avec les paramètres améliorés, en raison du calcul du RSSI qui effectue plus de traitement et utilise plus d'énergie. Después de un desarrollo exitoso en los servicios de atención médica, WBASN también se está utilizando en otros campos donde se requiere un monitoreo continuo y a distancia de la atención médica. Varios protocolos sugeridos presentados en la literatura trabajan para mejorar el rendimiento de WBASN centrándose en el retraso, la eficiencia energética y el enrutamiento. En esta investigación nos centramos en aumentar el periodo de estabilidad y el rendimiento, al tiempo que disminuimos el end-to-delay. Se utilizan dos nodos sumidero y se introduce el concepto de AnyCasting. En esta investigación, hemos presentado un esquema AnyCasting In Dual Sink (ACIDS) para WBASN y lo hemos comparado con los protocolos existentes LAEEBA y DARE. Se encuentra que el rendimiento de LOS ÁCIDOS es 51% y 13% eficiente que LAEEBA y DARE, respectivamente, en el rendimiento. Los resultados muestran que, el período de estabilidad de LOS ÁCIDOS es mucho mayor que el LAEEBA y SE ATREVEN con un retraso mínimo. El parámetro de energía en ÁCIDOS está en equilibrio con los parámetros mejorados, debido al cálculo de RSSI que procesa más y utiliza más energía. After successful development in health-care services, WBASN is also being used in other fields where continuous and distant health-care monitoring is required. Various suggested protocols presented in literature work to enhance the performance of WBASN by focusing on delay, energy efficiency and routing. In this research we focus to increase the stability period and throughput, while decreasing end-to-delay. Two sink nodes are utilized and concept of AnyCasting is introduced. In this research, we have presented a scheme AnyCasting In Dual Sink (ACIDS) for WBASN and compared it with existing protocols LAEEBA and DARE. The performance of ACIDS is found to be 51% and 13% efficient than LAEEBA and DARE respectively in throughput. Results show that, the stability period of ACIDS is much greater than LAEEBA and DARE with minimum delay. Energy parameter in ACIDS is in tradeoff with the improved parameters, due to the computation of RSSI which does more processing and utilizes more energy. بعد التطوير الناجح في خدمات الرعاية الصحية، يتم استخدام WBASN أيضًا في مجالات أخرى تتطلب مراقبة الرعاية الصحية المستمرة والبعيدة. تعمل البروتوكولات المقترحة المختلفة المقدمة في الأدبيات على تعزيز أداء WBASN من خلال التركيز على التأخير وكفاءة الطاقة والتوجيه. نركز في هذا البحث على زيادة فترة الاستقرار والإنتاجية، مع تقليل التأخير من البداية إلى النهاية. يتم استخدام عقدتي بالوعة ويتم تقديم مفهوم AnyCasting. في هذا البحث، قدمنا مخططًا لـ AnyCasting في حوض مزدوج (أحماض) لـ WBASN وقارناه بالبروتوكولات الحالية LAEEBA و DARE. وجد أن أداء الأحماض فعال بنسبة 51 ٪ و 13 ٪ من LAEEBA و DARE على التوالي في الإنتاجية. تظهر النتائج أن فترة استقرار الأحماض أكبر بكثير من LAEEBA وتجرؤ بأقل تأخير. متغير الطاقة في الأحماض في مقايضة مع المعلمات المحسنة، وذلك بسبب حساب RSSI الذي يفعل المزيد من المعالجة ويستخدم المزيد من الطاقة.

Demand Response (DR) programs under the umbrella of Demand Side Management (DSM) tend to involve end users in optimizing their Power Consumption (PC) patterns and offer financial incentives to shift the load at “low-priced” hours. However, users have their own preferences of anticipating the amount of consumed electricity. While installing an Energy Management System (EMS), the user must be assured that this investment gives optimum comfort of bill savings, as well as appliance utility considering Time of Use (ToU). Moreover, there is a difference between desired load distribution and optimally-scheduled load across a 24-h time frame for lowering electricity bills. This difference in load usage timings, if it is beyond the tolerance level of a user, increases frustration. The comfort level is a highly variable phenomenon. An EMS giving optimum comfort to one user may not be able to provide the same level of satisfaction to another who has different preferences regarding electricity bill savings or appliance utility. Under such a diversity of human behaviors, it is difficult to select an EMS for an individual user. In this work, a numeric performance metric,“User Comfort Level (UCL)”isformulatedonthebasisofuserpreferencesoncostsaving,toleranceindelayregardinguse of an appliance and return of investment. The proposed framework (UCL) allows the user to select an EMS optimally that suits his.her preferences well by anticipating electricity bill reduction, tolerable delay in ToU of the appliance and return on investment. Furthermore, an extended literature analysis is conducted demonstrating generic strategies of EMSs. Five major building blocks are discussed and a comparative analysis is presented on the basis of the proposed performance metric.

In this work, we propose a Realistic Scheduling Mechanism (RSM) to reduce user frustration and enhance appliance utility by classifying appliances with respective constraints and their time of use effectively. Algorithms are proposed regarding functioning of home appliances. A 24 hour time slot is divided into four logical sub-time slots, each composed of 360 min or 6 h. In these sub-time slots, only desired appliances (with respect to appliance classification) are scheduled to raise appliance utility, restricting power consumption by a dynamically modelled power usage limiter that does not only take the electricity consumer into account but also the electricity supplier. Once appliance, time and power usage limiter modelling is done, we use a nature-inspired heuristic algorithm, Binary Particle Swarm Optimization (BPSO), optimally to form schedules with given constraints representing each sub-time slot. These schedules tend to achieve an equilibrium amongst appliance utility and cost effectiveness. For validation of the proposed RSM, we provide a comparative analysis amongst unscheduled electrical load usage, scheduled directly by BPSO and RSM, reflecting user comfort, which is based upon cost effectiveness and appliance utility.

A wireless-powered cooperative energy aware anycast routing protocol is proposed in this work. In contrary to conventional cooperative networks, it is considered here that all the relays did not have embedded energy supply, rather equipped with rechargeable batteries and energy harvesting units. Hence, from source signals, they accumulate sufficient harvested energy before the information is forwarded to its destination. Each relay between two basic modes will switch adaptively, which are information forwarding and energy harvesting. The research is limited to decode-and-forward scheme and fixed ratio combining, which works at the relay node of the network and the receiver end, respectively. The physical layer cooperative diversity and network layer multi-hop routing lead us to devise a minimum energy routing protocol as the joint optimization of power required for transmission at physical layer and also at network layer for the process to select a link. Simulating our algorithm demonstrates that the suggested cooperative energy aware anycast routing scheme has a better end-to-end delay and better ratio of packet delivery. Results further reveal that our proposed algorithm has improved energy consumption in comparison to the non-cooperative energy aware anycast scheme and the cooperation-based robust cooperative routing protocol scheme. Sensed data are allocated between nearby nodes by cooperative energy aware anycast routing in a cost-effective way in order to achieve maximum network lifetime.

In various fields, the internet of things (IoT) gains a lot of popularity due to its autonomous sensors operations with the least cost. In medical and healthcare applications, the IoT devices develop an ecosystem to sense the medical conditions of the patients' such as blood pressure, oxygen level, heartbeat, temperature, etc. and take appropriate actions on an emergency basis. Using it, the healthcare-related data of patients is transmitted towards the remote users and medical centers for post-analysis. Different solutions have been proposed using Wireless Body Area Network (WBAN) to monitor the medical status of the patients based on low powered biosensor nodes, however, preventing increased energy consumption and communication costs are demanding and interesting problems. The issue of unbalanced energy consumption between biosensor nodes degrades the timely delivery of the patient's information to remote centers and gives a negative impact on the medical system. Moreover, the sensitive data of the patient is transmitting over the insecure Internet and prone to vulnerable security threats. Therefore, data privacy and integrity from malicious traffic are another challenging research issue for medical applications. This research article aims to a proposed secure and energy-efficient framework using Internet of Medical Things (IoMT) for e-healthcare (SEF-IoMT), which primary objective is to decrease the communication overhead and energy consumption between biosensors while transmitting the healthcare data on a convenient manner, and the other hand, it also secures the medical data of the patients against unauthentic and malicious nodes to improve the network privacy and integrity. The simulated results exhibit that the proposed framework improves the performance of medical systems for network throughput by 18%, packets loss rate by 44%, end-to-end delay by 26%, energy consumption by 29%, and link breaches by 48% than other states of the art solutions.

In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput.