Power Aware Routing in Mobile Ad Hoc Networks

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. This paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

https://ieeexplore.ieee.org/ielaam/5165411/8075182/7990560-aam.pdf

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

By broadcasting messages about traffic status to vehicles wirelessly, a vehicular ad hoc network (VANET) can improve traffic safety and efficiency. To guarantee secure communication in VANETs, security and privacy issues must be addressed before their deployment. The conditional privacy-preserving authentication (CPPA) scheme is suitable for solving security and privacy-preserving problems in VANETs, because it supports both mutual authentication and privacy protection simultaneously. Many identity-based CPPA schemes for VANETs using bilinear pairings have been proposed over the last few years to enhance security or to improve performance. However, it is well known that the bilinear pairing operation is one of the most complex operations in modern cryptography. To achieve better performance and reduce computational complexity of information processing in VANET, the design of a CPPA scheme for the VANET environment that does not use bilinear paring becomes a challenge. To address this challenge, we propose a CPPA scheme for VANETs that does not use bilinear paring and we demonstrate that it could supports both the mutual authentication and the privacy protection simultaneously. Our proposed CPPA scheme retains most of the benefits obtained with the previously proposed CPPA schemes. Moreover, the proposed CPPA scheme yields a better performance in terms of computation cost and communication cost making it be suitable for use by the VANET safety-related applications.

An Efficient Identity-Based Conditional Privacy-Preserving Authentication Scheme for Vehicular Ad Hoc Networks

Energy sustainability and environmental preservation have become worldwide concerns with the many manifestations of climate change and the continually increasing demand for energy. As cities and nations become more technologically advanced, electricity consumption rises to levels that may no longer be manageable if left unattended. The Smart Grid offers an answer to the shift to more sustainable technologies such as distributed generation and microgrids. A general public awareness and adequate attention from potential researchers and policy makers is crucial. This paper presents an overview of the Smart Grid with its general features, functionalities and characteristics. It presents the Smart Grid fundamental and related technologies and have identified the research activities, challenges and issues. It demonstrates how these technologies have shaped the modern electricity grid and continued to evolve and strengthen its role in the better alignment of energy demand and supply. Smart Grid implementation and practices in various locations are also unveiled. Concrete energy policies facilitate Smart Grid initiatives across the nations. Interestingly, Smart Grid practices in different regions barely indicate competition but rather an unbordered community of similar aspirations and shared lessons.

A review of the development of Smart Grid technologies

A survey on smart grid technologies and applications

Electric vehicles (EVs) are being introduced by different manufacturers as an environment-friendly alternative to vehicles with internal combustion engines, with several benefits. The number of EVs is expected to grow rapidly in the coming years. However, uncoordinated charging of these vehicles can put a severe stress on the power grid. The problem of charge scheduling of EVs is an important and challenging problem and has seen significant research activity in the last few years. This review covers the recent works done in the area of scheduling algorithms for charging EVs in smart grid. The works are first classified into two broad classes of unidirectional versus bidirectional charging, and then, each class is further classified based on whether the scheduling is centralized or distributed and whether any mobility aspects are considered or not. It then reviews the key results in this field following the classification proposed. Some interesting research challenges that can be addressed are also identified.

A Review of Charge Scheduling of Electric Vehicles in Smart Grid

Self-stabilization provides a non-masking approach to fault tolerance. Given this fact, one would hope that in a self-stabilizing system, the amount of disruption caused by a fault is proportional to the severity of the fault. However, this is not true for many self-stabilizing systems. Our paper addresses this weakness of distributed self-stabilizing systems by introducing the notion of fault containment. Informally, a fault-containing self-stabilizing algorithm is one that contains the effects of limited transient faults while retaining the property of self-st abilization. The paper begins with a formal framework for specifying and evaluating fault-containing self-stabilizing protocols. Then, it is shown that self-stabilization and fault containment are goals that can conflict. For example, it is shown that imposing a O(1) bound on the worst case recovery time from a l-faulty state necessitates added overhead for stabilization: for some tasks, the O(1) recovery time implies sfiabilization time cannot be within O(1) rounds from the optimum value. The paper then presents a transformer T that maps any non-reactive self-stabilizing algorithm P into an equivalent fault-containing self-stabilizing algorithm Pf that can repair any l-faulty state in O(1) time with O(1) space overhead. This transformation is baaed on a novel stabilizing timer paradigm that significantly simplifies the ti=k of fault containment. The paper concludes by generalizing the transformer ‘T into a parameterized transformer 7(k) such that for varying k we obtain varying performance measures for Pf.

Fault-containing self-stabilizing algorithms

Misbehavior detection schemes (MDSs) form an integral part of misbehaving node eviction in vehicular ad hoc networks (VANETs). A misbehaving node can send messages corresponding to an event that either has not occurred (possibly out of malicious intent), or incorrect information corresponding to an actual event (for example, faulty sensor reading), or both, causing applications to malfunction. While identifying the presence of misbehavior, it is also imperative to extract the root-cause of the observed misbehavior in order to properly assess the misbehavior's impact, which in turn determines the action to be taken. This paper uses the Post Crash Notification (PCN) application to illustrate the basic considerations and the key factors affecting the reliability performance of such schemes. The basic cause-tree approach is illustrated and used effectively to jointly achieve misbehavior detection as well as identification of its root-cause. The considerations regarding parameter tuning and impact of mobility on the performance of the MDS are studied. The performance of the proposed MDS is found to be not very sensitive to slight errors in parameter estimation.

Detecting misbehaviors in VANET with integrated root-cause analysis

Plug-in electric vehicles (PEVs) are emerging as an eco-friendly and cost-effective alternative to conventional vehicles driven by internal combustion engines. However, uncoordinated charging of a large number of PEVs may cause grid failure. Therefore, charge scheduling of PEVs is an important problem. However, the charge scheduling by a single aggregator does not scale well as the PEV population grows. We propose a distributed framework for efficient PEV charging with multiple aggregators in a city where a PEV raises its charging request to a specific aggregator, and each aggregator has partial information about others. The aggregators collaborate among themselves for scheduling PEVs for charging in different charging stations owned by it or others. In this paper, we formulate a bi-objective charge scheduling optimization problem that attempts to maximize the total profit of the aggregators while maximizing the total number of PEVs charged. We first prove that the problem is NP-complete. We then propose distributed offline and online algorithms to solve the problem, and present simulation results for some realistic traffic scenarios.

Distributed Charge Scheduling of Plug-In Electric Vehicles Using Inter-Aggregator Collaboration

In any vehicular adhoc network, there is always a possibility of incorrect messages being transmitted either due to faulty sensors and/or intentional malicious activities. Detecting and evicting sources of such misbehavior is an important problem. We observe that the performance of misbehavior detection schemes will depend on the application under consideration and the mobility dynamics of the detecting vehicle. Further, the underlying tradeoff in any such detection algorithm is the balance between False Positives and False Negatives; one would like to detect as many misbehaviors as possible, while at the same time ensuring that the genuine vehicles are not wrongly accused.

In this work we propose and analyze (via simulations) the performance of a Misbehavior Detection Scheme (MDS) for Post Crash Notification (PCN) application. We observe that the performance of this proposed scheme is not very sensitive to the exact dynamics of the vehicle on small scales, so that slight error in estimating the dynamics of the detecting vehicle does not degrade the performance of the MDS.

Arobinda Gupta

Papers

A Review of Charge Scheduling of Electric Vehicles in Smart Grid

Fault-containing self-stabilizing algorithms

Detecting misbehaviors in VANET with integrated root-cause analysis

Distributed Charge Scheduling of Plug-In Electric Vehicles Using Inter-Aggregator Collaboration

Distributed Misbehavior Detection in VANETs