Grid-based energy-aware routing in wireless sensor networks

The model of energy cost in a wireless sensor network （WSN）environment is built, and the energy awareness and the wireless interference mainly due to different path loss models are studied. A special case of a clustering scheme, a twodimensional grid clustering mechanism, is adopted. Clusterheads are rotated evenly among all sensor nodes in an efficient and decentralized manner, based on the residual energy in the battery and the random backoff time. In addition to transmitting and receiving packets within the sensors＇ electrical and amplification circuits, extra energy is needed in the retransmission of packets due to packet collisions caused by severe interference. By analysis and mathematical derivation, which are based on planar geometry, it is shown that the total energy consumed in the network is directly related to the gridstructure in the proposed grid based clustering mechanism. The transmission range is determined by cluster size, and the path loss exponent is determined by nodal separation. The summation of overall interference is caused by all the sensors that are transmitting concurrently. By analysis and simulation, an optimal grid structure with the corresponding grid size is presented, which balances between maximizing energy conservation and minimizing overall interference in wireless sensor networks.

An Anonymous Authentication Scheme for Plugin Electric Vehicles Joining to Charging/Discharging Station in Vehicle-to-Grid(V2G) Networks

Incorporating electric vehicles into smart grid,vehicle-to-Grid(V2G) makes it feasible to charge for large-scale electric vehicles,and in turn support electric vehicles,as mobile and distributed storage units,to discharge to smart grid.In order to provide reliable and efficient services,the operator of V2 G networks needs to monitor realtime status of every plug-in electric vehicle(PEV) and then evaluate current electricity storage capability.Anonymity,aggregation and dynamic management are three basic but crucial characteristics of which the services of V2 G networks should be.However,few of existing authentication schemes for V2 G networks could satisfy them simultaneously.In this paper,we propose a secure and efficient authentication scheme with privacy-preserving for V2 G networks.The scheme makes the charging/discharging station authenticate PEVs anonymously and manage them dynamically.Moreover,the monitoring data collected by the charging/discharging station could be sent to a local aggregator(LAG)in batch mode.In particular,time overheads during verification stage are independent with the number of involved PEVs,and there is no need to update the membership certificate and key pair before PEV logs out.

Phosphorus:Distributed Control Plane Approach for Photonic Grids

G2MPLS is a Network Control Plane(NCP) architecture that implements the concept of Grid Network Services(GNS) required for implementing photonic Grids.It provides part of the functionalities related to the selection,co-allocation and maintenance of both Grid and network resources through a set of seamless procedures at the user-to-network and inter-domain boundaries.G2MPLS' main features and procedures are presented in this document,as well as the considerations to deploy it and facilitate its dissemination.

Central Aggregator Intrusion Detection System for Denial of Service Attacks

Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles(EVs)to be used by the smart grid through the central aggregator.Since the central aggregator is connected to the smart grid through a wireless network,it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system.However,existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network.In this paper,the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of the vehicle-to-grid network is investigated and an intrusion detection system for the vehicle-to-grid network is proposed.The proposed system,central aggregator–intrusion detection system(CA-IDS),works as a security gateway for EVs to analyze andmonitor incoming traffic for possible DoS attacks.EVs are registered with a Central Aggregator(CAG)to exchange authenticated messages,and malicious EVs are added to a blacklist for violating a set of predefined policies to limit their interaction with the CAG.A denial of service(DoS)attack is simulated at CAG in a vehicle-to-grid(V2G)network manipulating various network parameters such as transmission overhead,receiving capacity of destination,average packet size,and channel availability.The proposed system is compared with existing intrusion detection systems using different parameters such as throughput,jitter,and accuracy.The analysis shows that the proposed system has a higher throughput,lower jitter,and higher accuracy as compared to the existing schemes.

Electricity Services Based Dependability Model of Power Grid Communication Networking

The technology of Ultra-High Voltage （UHV） transmission requires higher dependability for electric power grid. Power Grid Communication Networking （PGCN）, the fundamental information infrastructure, severs data transmission including control signal, protection signal, and common data services. Dependability is the necessary requirement to ensure services timely and accurately. Dependability analysis aims to predicate operation status and provide suitable strategies getting rid of the potential dangers. Due to the dependability of PGCN may be affected by external environment, devices quality, implementation strategies, and so on, the scale explosion and the structure complexity make the PGCN＇s dependability much challenging. In this paper, with the observation of interdependency between power grid and PGCN, we propose an electricity services based dependability analysis model of PGCN. The model includes methods of analyzing its dependability and procedures of designing the dependable strategies. We respectively discuss the deterministic analysis method based on matrix analysis and stochastic analysis model based on stochastic Petri nets.

Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems

The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.

Simulation and analysis of the carrying capacity for road networks using a grid-based approach

The number of vehicles that a road network can carry is limited.When the limit is exceeded,the network system is not able to function effectively.In this paper,an updated cellular automaton model for grid networks with all-way stop-controlled intersections is proposed to simulate the network level critical density and carrying capacity under different conditions,which essentially indicates the limit number of vehicles that the network can handle before going into gridlock.In the proposed model,two update rules,including lane-changing and the longitudinal location update,are adopted to describe the vehicle’s movements on road segments according to the driving condition on the road and the vehicle’s direction in the downstream intersection.The vehicle’s movements in intersection areas are prioritized based on vehicle’s position,so as to prevent collisions within the intersection area.The simulation results show that an increase in network size is able to expand the carrying capacity of a road network,whereas the expansion rate is lower than the change rate in the network size.The carrying capacity is also associated with the structure of road network.The carrying capacity is inversely proportional to the number of intersections,and proportional to the length of the road in the network.Also,optimizing the origin-destination(O-D)distribution can increase the carrying capacity of an urban road network.

Remote Measurement in Steel Grid Structure Based on Control Grid Network

Based on a control grid network and in combination with a remote total station and digital camera,the distribution of steel nodes and deflection curve of a steel grid structure can be obtained easily.The measurement result shows that this method is effective and utilitarian.

Exponentially Expanded Grid Network Approach (EEGNA): An Efficient Way for the Simulation of Stiff Electrochemical Problems

The exponentially expanded space grid was incorporated into the network approach to overcome the problem of low simulation efficiency during the simulations of electrochemical problems with stiff kinetics or wide dispersion of diffusion coefficients, resulting in an effective electrochemical simulation method: exponentially expanded grid network approach (EEGNA). The stability and accuracy of the EEGNA for the simulation of various electrode processes coupled with different types of homogeneous reactions were investigated.