Wireless sensor network (WSN) is a group of several autonomous sensor nodes attached to each other. Wireless sensor networks are commonly used in a lot of applications and are expected to have a cheap deployment cost. The network of sensors continues to grow aiding the need of the system. Due to that, sensors become vulnerable to attacks and need strong security mechanism. To strengthen the security of data which are transmitted through sensors in WSN, different cryptographic schemes are used. As WSN has limited energy source, therefore, complex cryptographic algorithms may require excessive computational time which not only make the data transmission slow but the life time of sensor network will be significantly affected. To overcome these challenges a new hybrid cryptographic scheme, AES and Modified Playfair Cipher (AMPC), is introduced in this paper.
In distributed systems, a single node (referred to as a leader) coordinates all other nodes to ensure synchronization. If this node fails, another node in the system must adopt the role of leader. The classic bully algorithm suffers from some significant drawbacks, such as excessive message passing, a redundant number of election calls, and uncertainties over message delivery. The enhanced bully algorithm is one of the most recent improvements of this algorithm. However, this algorithm performs poorly in average- and worst-case scenarios. In this paper, a novel waiting time-based algorithm is proposed to improve the enhanced bully algorithm for electing a new leader during such critical scenarios. In this algorithm, if a single or multiple number of nodes discover that the leader has failed, it does not broadcast instantly. Rather, it waits for a certain period, and this waiting time is assigned to the nodes according to their load. After the timeout, the node sends its message and starts the election process. Moreover, it restricts nodes from unnecessary message passing and stops any redundant election calls. Accordingly, this algorithm detects the failure of the leader node more precisely and elects a new leader more quickly.
Electric vehicle charging stations (EVCS) play a vital role in providing charging support to EV users. In order to facilitate users in terms of charging speed and price, two different charging modes (L2 and L3) are currently available at public charging stations. L3 mode provides quick charging with higher power, whereas L2 mode offers moderate charging speed with low power. The integration of an EVCS into the power grid requires coordinated charging strategies in order to reduce the electricity bill for a profitable operation. However, the effective utilization of the multi-mode charging strategy to serve the maximum number of EVs for a small charging station with limited charging capacity and spots is an open issue. To this end, we propose a priority-based online charging scheme, namely PBOS, which is based on real-time information and does not depend on future knowledge. The objective is to serve as many vehicles as possible in a day while fulfilling their charging requirements under a multi-mode EVCS setting and reducing the charging costs by utilizing the timeof-use pricing based demand response strategy. Extensive simulation is done while considering two different demand response strategies under various settings. The results show that the proposed algorithm can increase profit for the EVCS by up to 48% with a 22% lower rejection rate. In addition, it can serve EVs with a low battery charge, known as state of charge (SOC), up to 11% higher than most of the other schemes and can save up to 81.75 minutes to attain the same SOC when compared with other schemes.
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