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In this problem, we have considered a city map network with a Centralised Charging Station (CCS) and a number of Battery Swapping Stations (BSSs). The CCS owns a set of delivery trucks with limited capacity. Each BSS can demand some fully charged batteries from the CCS, which needs to figure out a routing strategy for each of the delivery trucks. The strategy fulfills the demand of each BSS and at the same time optimizes the overall cost of delivery in terms of the distance travelled. A constrained programming based approach has been proposed to obtain an optimal routing of the delivery trucks considering the partial delivery of batteries.

In this paper, we address one of the many challenges of electric vehicles(EVs) that is the optimal placement of charging stations(citing) and allocating a certain number of charging ports(sizing) at these stations. We formulate a real life problem in the form of a city network that accounts for the uncertainty in the arrival of EVs, mathematically represented in the form of an optimization problem. The uncertainty in the flow of EVs can be approximated in a statistical distribution which can be analysed to determine the optimal allocation of the charging ports. Experiments suggest that our approach performs better when compared using certain performance metric with the existing research works.

We consider the problem of efficient scheduling of vehicle-to-grid (V2G), grid-to-vehicle (G2V), vehicle-to-vehicle (V2V) operations in a smart microgrid equipped with renewable energy resources and multiple types of charging ports to cater the requirements of Electric Vehicles (EVs) and essential loads of households. Our objective is to schedule the operations such that the total price paid to the utility-grid for the electrical energy is minimum. We propose a mixed integer linear programming (MILP) based formulation to obtain an optimal schedule of those operations. We present a heuristic approach to find a reasonable solution quickly.

We propose a coordinated scheduling approach for controllable electrical appliances along with the optimal usage of heterogeneous energy sources to minimize the energy drawn from the grid and thereby reducing electricity cost for the users. A mixed integer linear programming (MILP) formulation for the problem is presented to produce the optimal solutions, and an efficient heuristic algorithm is proposed to obtain results efficiently.

We propose an efficient charge scheduling and routing mechanism for a set of electric vehicles with the objective to optimize average time and energy consumption for a tour. We propose a graph-based offline heuristic scheduling algorithm, whose performance evaluation is done in comparison to optimal results on graphs depicting real world scenario. Obtained preliminary results indicate that the proposed algorithm is highly efficient and effective in producing solutions that are significantly closer to optimal solutions.

Traditionally the passwords are stored in hashed format. However, if the password file is compromised then by using the brute force attack there is a high chance that the original passwords can be leaked. False passwords -- also known as honeywords, are used to protect the original passwords from such leak. A good honeyword system is dependent on effective honeyword generation techniques. In this paper, the risk and limitations of some of the existing honeyword generation techniques have been identified as different notes. Three concepts -- modified tails, close number formation and caps key are introduced to address the existing issues. The experimental analysis shows that the proposed techniques with some preprocessing can protect high percentage of passwords. Finally a comparative analysis is presented to show how the proposed approaches stand with respect to the existing honeyword generation approaches.

An access control system is often viewed as a state transition system. Given a set of access control policies, a general safety requirement in such a system is to determine whether a desirable property is satisfied in all the reachable states. Such an analysis calls for formal verification. While formal analysis on traditional RBAC has been done to some extent, the extensions of RBAC lack such an analysis. In this paper, we propose a formal technique to perform security analysis on the Generalized Temporal RBAC (GTRBAC) model which can be used to express a wide range of temporal constraints on different RBAC components like role, user and permission. In the proposed approach, at first the GTRBAC system is mapped to a state transition system built using timed automata. Characteristics of each role, user and permission are captured with the help of timed automata. A single global clock is used to express the various temporal constraints supported in a GTRBAC model. Next, a set of safety and liveness properties is specified using computation tree logic (CTL). Model checking based formal verification is then done to verify the properties against the model to determine if the system is secure with respect to a given set of access control policies. Both time and space analysis has been done for studying the performance of the approach under different configurations.