Ankur Sarker

An Efficient Wireless Power Transfer System to Balance the State of Charge of Electric Vehicles

As an alternate form in the road transportation system, electric vehicle (EV) can help reduce the fossil-fuel consumption. However, the usage of EVs is constrained by the limited capacity of battery. Wireless Power Transfer (WPT) can increase the driving range of EVs by charging EVs in motion when they drive through a wireless charging lane embedded in a road. The amount of power that can be supplied by a charging lane at a time is limited. A problem here is when a large number of EVs pass a charging lane, how to efficiently distribute the power among different penetrations levels of EVs? However, there has been no previous research devoted to tackling this challenge. To handle this challenge, we propose a system to balance the State of Charge (called BSoC) among the EVs. It consists of three components: i) fog-based power distribution architecture, ii) power scheduling model, and iii) efficient vehicle-to-fog communication protocol. The fog computing center collects information from EVs and schedules the power distribution. We use fog closer to vehicles rather than cloud in order to reduce the communication latency. The power scheduling model schedules the power allocated to each EV. In order to avoid network congestion between EVs and the fog, we let vehicles choose their own communication channel to communicate with local controllers. Finally, we evaluate our system using extensive simulation studies in Network Simulator-3, MatLab, and Simulation for Urban MObility tools, and the experimental results confirm the efficiency of our system.

Probabilistic Network-Aware Task Placement for MapReduce Scheduling

Maximizing data locality in task scheduling is critical for the performance of MapReduce job execution. Manyexisting works on MapReduce scheduling decide the placementof map and reduce tasks on a coarse granularity of locationsmeasured by located machines and racks. They do not explicitlyconsider the network topology and data transmission cost, whichmay cause task straggling and degrade the job performance. Inorder to improve MapReduce job performance, in this paper, we consider the task placement with the goal of minimizing theoverall data transmission cost for a job execution while balancingthe transmission cost reduction and resource utilization. Wepropose a probabilistic network-aware scheduling algorithm thatselects a task (map task or reduce task) to be scheduled on a givenavailable task slot that leads to the minimum transmission costamong the task candidates, and then schedule the selected taskon the slot with a probability determined by its transmission cost, a lower expected transmission cost leads to a higher probabilityand vice versa. We also propose a method to more accuratelyestimate the intermediate data size based on the progress ofmap tasks, which is needed to calculate the transmission cost ofreduce tasks but is unknown at the time of reduce task scheduling. We implement our probabilistic network-aware schedulingalgorithm on Apache Hadoop and conduct experiments on ahigh-performance computing platform. The experimental resultsshow that our scheduling algorithm outperforms the previousapproaches in terms of job completion time and cluster resource utilization.

Realization of Reversible Logic in DNA Computing

In this paper, DNA-based Toffoli gate has been modeled using the formation of DNA characteristics. After that, the logics of the basic (AND, OR, NOT) gates and EX-OR gates have been realized using our DNA-based Tofffoli gate. The proposed DNA-based Tofolli gate is faster due to parallelism and replication properties of DNA strands. The proposed gate also requires less space because of the compactness of DNA strands. Moreover, the DNA-based Tofolli gate requires low power as the formation of DNA consumes a small amount of energy. Reversible DNA-based composite logic has also been accomplished by a reversible Half-Adder circuit. Finally, a comparative study between the existing Toffoli gate and our proposed DNA-based Toffili gate has been done.

A Decentralized Network with Fast and Lightweight Autonomous Channel Selection in Vehicle Platoons for Collision Avoidance

Always keeping a certain distance between vehicles in a platoon is important for collision avoidance. Centralized platoon systems let the leader vehicle determine and notify the velocities of all the vehicles in the platoon. Unfortunately, such a centralized method generates high packet drop rate and communication delay due to the leader vehicles limited communication capability. Therefore, we propose a decentralized platoon network, in which each vehicle determines its own velocity by only communicating with the vehicles in a short range. However, the multiple simultaneous transmissions between different pairs of vehicles may interfere with each other. Directly applying current channel allocation methods for interference avoidance leads to high communication cost and delay in vehicle joins and departures (i.e., vehicle dynamics). As a result, a challenge is how to reduce the communication delay and cost for channel allocation in decentralized platoon networks? To handle this challenge, by leveraging a typical feature of a platoon, we devise a channel allocation algorithm, called the Fast and Lightweight Autonomous channel selection algorithm (FLA), in which each vehicle determines its own channel simply based on its distance to the leader vehicle. We conduct experiments on NS-3 and Matlab to evaluate the performance of our proposed methods. The experimental results demonstrate the superior performance of our decentralized platoon network over the previous centralized platoon networks and of FLA over previous channel allocation methods in platoons.

A novel approach to design a reversible shifter circuit using DNA

Traditional silicon computers are believed to consume more power compared to computing systems based on Deoxyribonucleic Acid (DNA). In addition, DNA-based logic gates are stable, reusable and also outperform the non-DNA based existing shifters. In this paper, a new approach for designing DNA-based reversible shifter circuit is proposed where any kind of shifting operations can be carried out. The proposed DNA-based reversible shifter circuit is comparatively faster due to parallelism and replication properties of DNA strands. It also requires less space because of the compactness of DNA strands.

Opportunistic Energy Sharing Between Power Grid and Electric Vehicles: A Game Theory-Based Pricing Policy

Electric vehicles (EVs) have great potential to reduce dependency on fossil fuels. The recent surge in the development of online EV (OLEV) will help to address the drawbacks associated with current generation EVs, such as the heavy and expensive batteries. OLEVs are integrated with the smart grid of power infrastructure through a wireless power transfer system (WPT) to increase the driving range of the OLEV. However, the integration of OLEVs with the grid creates a tremendous load for the smart grid. The demand of a power grid changes over time and the price of power is not fixed throughout the day. There should be some congestion avoidance and load balancing policy implications to ensure quality of services for OLEVs. In this paper, first, we conduct an analysis to show the existence of unpredictable power load and congestion because of OLEVs. We use the Simulation for Urban MObility tool and hourly traffic counts of a road section of the New York City to analyze the amount of energy OLEVs can receive at different times of the day. Then, we present a game theory based on a distributed power schedule framework to find the optimal schedule between OLEVs and smart grid. In the proposed framework, OLEVs receive the amount of power charging from the smart grid based on a power payment function which is updated using best response strategy. We prove that the updated power requests converge to the optimal power schedule. In this way, the smart grid maximizes the social welfare of OLEVs, which is defined as mixed consideration of total satisfaction and its power charging cost. Finally, we verify the performance of our proposed pricing policy under different scenarios in a simulation study.

Quick and Autonomous Platoon Maintenance in Vehicle Dynamics For Distributed Vehicle Platoon Networks

Platoon systems, as a type of adaptive cruise control systems,will play a significant role to improve travel experience androadway safety. The stability of a platoon system is crucialso that each vehicle maintains a safety distance from itsproceeding vehicle and can take necessary actions to avoidcollisions. However, current centralized platoon maintenancemethod cannot meet this requirement. We suggest to use adecentralized platoon maintenance method, in which eachvehicle communicates with its neighbor vehicles and self-determines its own velocity. However, a vehicle needs toknow its distance from its preceding vehicle to determineits velocity, which is unavailable in vehicle communicationdisconnection caused by vehicle dynamics (i.e., node joinsand departures). Thus, a formidable challenge is: how torecover the platoon quickly in vehicle dynamics even when thedistance information is unavailable? To handle this challenge,we first profile a succeeding vehicle’s velocity to minimizethe time to recover the connectivity hole with its precedingvehicle and find that the profiles are almost the same at thebeginning regardless of its current velocity and distance to itspreceding vehicle. Accordingly, we devise a strategy, in whicha succeeding vehicle uses its stored common velocity profilewhen it is disconnected from its preceding vehicle and thenadjusts its velocity once the connection is built. Experimentalresults from simulation show the efficiency and effectivenessof our decentralized platoon maintenance method.

Velocity Optimization of Pure Electric Vehicles with Traffic Dynamics Consideration

As Electric Vehicles (EVs) become increasingly popular, their battery-related problems (e.g., short driving range and heavy battery weight) must be resolved as soon as possible. Velocity optimization of EVs to minimize energy consumption in driving is an effective alternative to handle these problems. However, previous velocity optimization methods assume that vehicles will pass through traffic lights immediately at green traffic signals. Actually, a vehicle may still experience a delay to pass a green traffic light due to a vehicle waiting queue in front of the traffic light. In this paper, for the first time, we propose a velocity optimization system which enables EVs to immediately pass green traffic lights without delay. We collected real driving data on a 4.0 km long road section of US-25 highway to conduct extensive trace-driven simulation studies. The experimental results from Matlab and Simulation for Urban MObility (SUMO) traffic simulator show that our velocity optimization system reduces energy consumption by up to 17.5% compared with real driving patterns without increasing trip time.

Design of a DNA-based reversible arithmetic and logic unit

Owing to the emergence of better characteristics such as parallelism, low power consumption and data compactness, DNA computing has drawn great attention in recent years. In this study, the authors realise an arithmetic and logic unit (ALU) using deoxyribonucleic acid (DNA). Inputs and outputs of the proposed ALU keep the logical reversibility in computation processes. The proposed ALU is capable of performing four logical (AND, OR, EX-OR and NOT) with three arithmetic (addition, subtraction and multiplication) operations. They use DNA-based multiplexer to carry out final output. Compared to silicon-based computation, the proposed ALU is faster and requires less space and power due to parallelism, replication properties, compactness and formation of DNA strands. However, compared to one existing DNA-based system, fewer signals are required in each step. Besides, another existing DNA-based ALU requires five complex biological steps to compute, whereas the proposed ALU requires three biological steps. Also, the time complexities of that existing system are O(mln₂n) for addition and subtraction operations; O(m) for logical operations and O(m(ln₂n)(2)) for multiplication operation, while the proposed system has O(1) for logical operations and O(n) for others; here n is the number of bits and m is the number of test tubes for operands.

A novel approach for constructing reversible fault tolerant n-bit binary comparator

Nowadays fault tolerant reversible logic is becoming popular and have widely used in reducing power consumption of digital logic design. Reversible logic is used to optimize power by recovering bit loss from its unique input-output mapping. In this paper, for the first time we designed a novel approach for constructing fault tolerant reversible n-bit binary comparator. An algorithm has been presented for constructing the novel fault tolerant reversible comparator circuit. We designed two new fault tolerant reversible gates namely AG, and FTSEG to optimize the number of gates, garbage outputs, quantum cost, constant inputs and delay of the circuit. Two lemmas are also presented to prove the fault tolerance or parity preserving property for the proposed two fault tolerant reversible gates AG and FTSEG respectively. The simulation results of the proposed fault tolerant reversible design show that the circuit works correctly.