Elsevier

Computer Networks

Volume 153, 22 April 2019, Pages 36-48
Computer Networks

SURVIVOR: A blockchain based edge-as-a-service framework for secure energy trading in SDN-enabled vehicle-to-grid environment

https://doi.org/10.1016/j.comnet.2019.02.002Get rights and content

Abstract

Electric vehicles (EVs) have transformed the smart transportation sector by providing diverse energy management solutions to the smart grid. Energy trading among EVs and charging stations (CS) in a vehicle-to-grid (V2G) environment is one of the popular verticals in smart grid. However, processing the energy trading decisions at remote control centers lead to an increase in delay and network overhead. Apart from these issues, the security concerns while trading the energy in such an environment remain persistent. Therefore, to handle the aforementioned issues, this paper presents SURVIVOR: A Blockchain based Edge-as-a-Service Framework for Secure Energy Trading in software defined networking (SDN)-enabled V2G Environment. In the proposed framework, the energy trading decisions are processed closer to the location of EVs through edge nodes. Moreover, for securing the energy trading transactions, blockchain is used wherein the approver nodes are selected amongst all the present nodes on the basis of a utility function and are made responsible for validating the transactions. Once such nodes are selected, a consensus-based blockchain mechanism for secure energy trading in SDN-enabled V2G environment is presented. In this mechanism, edge nodes are responsible for generating proof-of-work puzzles. The proof-of-work is a unique hash value which is computed for each EV and the transactions for which the approver nodes compute the same proof-of-work for each EV are added in the blockchain. The complete scheme is backed by the SDN architecture to reduce the overall latency and increase the throughput of the smart transportation network. The results obtained prove that the proposed scheme is effective for trading the energy between EVs and CS while securing the underlying trading transactions using blockchain. Moreover, the communication and computation cost of the proposed scheme comes out to be small which proves that it can be used in real-world applications. The latency in the complete transportation sector is also greatly reduced by using the SDN-architecture.

Introduction

In the recent times, transportation sector has undergone a global transformation with the emergence of smart cities, thereby making it a smart transportation system. This system comprises of vehicles enabled with information and communication technologies (ICT) to provide various automated services such as-navigation, traffic control, parking, and information sharing. The communication technologies used for inter-vehicle communication are short to medium range communication protocols like IEEE 802.15.1, IEEE 802.15.4, IEEE 802.11 a/b/g/p; and for vehicle to service provider include long range communication protocols like IEEE 802.16, Long Term Evolution, etc. [1]. These vehicles may belong to the conventional fuel-based vehicles or the upcoming electric or plug-in electric vehicles (EVs).

The emergence of EVs has led to the drastic transition in the smart transportation sector. EVs have thrived in this transition as they provide manifold benefits apart from the transport services. The primary benefit of EVs in the smart transportation sector is that they can be used for energy sustainability of a smart city [2]. Moreover, the EVs are eco-friendly vehicles as they produce near-zero tapline carbon emissions and have less operating cost than the conventional fuel vehicles [3]. Because of these advantages, the number of EVs on the roads are exponentially increasing. The global trend in growth of EVs is shown in Fig. 1 and according to the Global EV outlook 2018, there will be more than 20 million EVs by 2020 [4]. The EVs are also an essential component in managing the energy needs of the smart city as the primary source of their fuel is energy. Therefore, one needs to manage their energy requirements in such a way that these EVs can be used as a carrier for self-sustainability in the smart cities. For example, if there is surplus energy in the city, this energy can be bought by the EVs and when the city faces energy deficit, EVs can supply the energy back to the system. Moreover, mismanagement of the energy demands of a large number of EVs can lead to power fluctuations in the smart city [5]. This problem is more prominent in developing countries where energy generation sources are limited, but the demand is increasing day by day. Therefore, one needs to leverage the vehicle-to-grid (V2G) capabilities of EVs to strike a balance between energy demand and supply.

However, there are many issues pertaining to the energy trading with EVs which restrict their participation in the V2G activities for energy management. For instance, the energy trading decisions have to made at remote control center, which in turn lead to delay and network overhead. However, in real-time communications, it is always preferable to handle the computational processing closer to the location of the user/EVs. Moreover, the time required to reach the destination (where trading would take place) and its distance from their present location are few of the factors which hinder the energy trading process. With the advances in technology, a new computing paradigm has emerged which can provide services at a rapid pace at a location closer to the end-users. This paradigm is known as edge computing and is considered closer to the end-user as compared to the traditional cloud computing architecture. Thus, edge can provide services relatively faster to the cloud which means that the quality of service is invariably enhanced.

Apart from these aspects, trust and security is always highly desirable. So, when the EVs trade for energy (to make a profit/fulfill their energy demands) over a remote server, the security concerns remain utmost importance to make a successful transaction. The incoming requests in the network should be authenticated prior to broadcasting for taking the energy trading decisions. Moreover, with the increased usage of ICT for communicating the energy trading requests, the security of the overall system needs to be robust. Because, the adversaries, if present in the network, should not be able to modify the transaction for their personal benefits. Moreover, implementing the conventional security mechanisms on the distributed edge nodes should be carefully considered so as not to jeopardize the overall security of the system. An adversary may act as an edge node and impact the entire energy trading mechanism thereby causing loss to both EVs and charging stations (CSs). Thus, the security mechanisms should be distributed in nature (so that no single entity is responsible for the system security) and lightweight (to reduce the additional burden on the system).

In this regard, blockchain has emerged as one of the most prominent technique to meet the security requirements of the system in an effective way [6], [7]. One of the most popular examples where blockchain has been primarily used for providing the security is the exchange of crypto-currency known as Bitcoin [8]. The blockchain is distributed in nature and does not depend on the single trusted third party to authenticate the incoming requests in the system [9]. So, it even works well in the scenarios where the centrally managed security schemes fail. Blockchain is a ledger-based mechanism which takes care of different security constraints related to confidentiality, integrity, and authentication. All the entities present in network maintain a ledger for keeping the information of all the valid transactions executing in the network. Whenever a new transaction arrives in the network, the entities present in the network authenticate it by solving a puzzle (also know as proof-of-work). So, the transaction is only added in the blockchain if the puzzle is correctly solved and authenticated by rest of the nodes.

While implementing the security and serving the energy trading requests in the smart transportation sector, the traditional network architecture suffers from the various drawbacks. Firstly, these are not able to dynamically re-configure the network topology for reducing the latency. Secondly, the network becomes overloaded when incoming requests increase as there is a fixed path for transmitting the data packet. Third, the networking functionality is mainly implemented on the devices such as switches and routers in a dedicated manner, so it is very difficult to update each device to make the network consistent in terms of updating policies. Therefore, to handle all these issues, a new networking paradigm has emerged which is capable of dynamic routing of packets and adapt to the changing network requirements. This paradigm is known as software-defined networking (SDN) where the complete system is divided into number of planes with each plane performing a specific task [10]. These planes are namely data, control, and application. All the forwarding devices are placed at the data plane, the control logic of the network is implemented at the control plane, and the applications such as packet routing, request forwarding, etc. are handled at the application plane.

To handle all the aforementioned issues, SURVIVOR: A Blockchain based Edge-as-a-Service Framework for Secure Energy Trading in SDN-enabled V2G Environment is presented in this paper. In this framework, the EVs select an edge node (from all available edge nodes) on the basis of utility functions. This selected edge node serves the EVs for handling their energy trading computational load. Using this edge-as-a-service platform, EVs trade for the required energy with the CSs deployed in the smart city. This platform significantly reduces the burden on EVs which have less computational resources and makes the complete process faster and on the edge of the network. Being a distributed and insecure layout, a consensus-based blockchain mechanism is used to authenticate the energy trading transactions in the system. The edge nodes (other than the one responsible for computation load of an EV) act as approver nodes for transaction authentication. The underlying paradigm follows openflow protocol to provision dynamic network policies in the distributed edge-as-a-service platform.

The following are the major contributions of the proposed research work.

  • An SDN based system model is designed for edge-as-a-service platform which follows openflow protocol to provision dynamic network policies in the distributed setup.

  • An edge-as-a-service platform is selected on the basis of different utility functions for energy trading between EVs and CSs in SDN-enabled V2G environment. An efficient algorithm responsible for convergence to an optimal solution is also designed.

  • A consensus based blockchain mechanism is designed for securing the energy trading transactions in distributed edge-as-a-service environment. In this scheme, the edge nodes other than the one selected to handle the computational workload of energy trading mechanism act as approver nodes.

The rest of the paper is organized as follows. Section 2 discusses the related work. Section 3 illustrates the complete system model of the scheme and Section 4 describes the proposed scheme in detail. Section 5 outlines the simulation results and the paper is concluded in Section 6.

Section snippets

Related work

This section is divided into various categories with emphasis on smart transportation and energy trading, edge-as-a-service, SDN in energy trading, and blockchain applications in energy trading.

System model

The comprehensive architecture of the proposed scheme is depicted in Fig. 2. There are primarily two participating entities in this architecture namely EVs and CSs. The EVs move to different CSs located at different locations on the basis of the various parameters such as distance, pricing, etc. which give the maximum profit to the EVs. This architecture is based on SDN and is responsible for providing the computation, control, and communication capabilities to all the EVs and CSs. In addition

Edge-as-a-service for secure energy trading using blockchain

The proposed scheme is classified into three parts; 1) In the first part, energy trading scheme between EVs and CSs is presented, 2) In the second part, a computational offloading scheme using edge-as-a-service is designed, and 3) Finally, a blockchain-based secure energy trading mechanism using edge-as-a-service is presented. All these parts are elaborated in the subsequent subsections.

Results and discussions

The case study of a city of 5 km  ×  5 km is considered which is considered for evaluating the proposed scheme which comprises of 4 CSs placed at different geographical locations and 40 EVs which can charge or discharge at any of the CSs based on their requirements. The EVs of different types are considered for energy trading with their battery specifications given in Table 4 [32]. The CSs are considered to be available for 24 h with ample charging points available for the EVs. The value of SoCk

Conclusion

This paper presents SURVIVOR: a blockchain based edge-as-a-service framework for secure energy trading in SDN-enabled V2G environment. Edge nodes are used to serve the EV request closer to their physical location. The SDN-enabled communication architecture is used to provide communication backbone to the complete smart transportation sector. This increases the overall throughput of the network by decreasing the network latency for passing the information among various nodes. Apart from it, the

Anish Jindal received his Bachelor of Technology degree from Punjab Technical University, India in 2012 and Master of Engineering degree from University Institute of Engineering and Technology, Panjab University, Chandigarh, India in 2014, both in Computer Science and Engineering. He received his Ph.D. degree in Computer Science and Engineering Department from Thapar University, Patiala (Punjab), India in 2018. He is working as a Senior Research Associate in the School of Computing and

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    Anish Jindal received his Bachelor of Technology degree from Punjab Technical University, India in 2012 and Master of Engineering degree from University Institute of Engineering and Technology, Panjab University, Chandigarh, India in 2014, both in Computer Science and Engineering. He received his Ph.D. degree in Computer Science and Engineering Department from Thapar University, Patiala (Punjab), India in 2018. He is working as a Senior Research Associate in the School of Computing and Communications, Lancaster University, UK. Prior to this, he was a Senior Research fellow of Council of Scientific and Industrial Research, India. He is member of the IEEE, ACM, and IAENG.

    Gagangeet Singh Aujla is working as an Associate Professor in Computer Science and Engineering Department, Chandigarh University, Mohali, Punjab, India. He received the B.Tech degree and the M.Tech degree in Computer Science and Engineering from Punjab Technical University, Jalandhar, Punjab, India, in 2003 and 2013, respectively. He received his Ph.D. in Computer Science and Engineering from Thapar Institute of Engineering and Technology, Patiala, Punjab, India in 2018. He received IEEE TCSC Outstanding Ph.D. Dissertation Award at Guangzhou, China in 2018. He has many research contributions in the area of smart grid, cloud computing, software defined networks, and security. He is member of the IEEE, and ACM.

    Neeraj Kumar received his Ph.D. in CSE from Shri Mata Vaishno Devi University, Katra (J & K), India, and was a postdoctoral research fellow in Coventry University, Coventry, UK. He is working as an Associate Professor in the Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala (Punjab), India. He has published more than 200 technical research papers in leading journals and conferences. He is the Technical Editor of IEEE Network Magazine, an Associate Technical Editor of IEEE Communication Magazine and an Associate Editor of IJCS, Wiley, JNCA, Elsevier, and Security & Communication, Wiley. He is senior member of the IEEE.

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