Distributed denial of service (DDoS) attacks in cloud computing environments are growing due to the essential characteristics of cloud computing. With recent advances in software-defined networking (SDN), SDN-based cloud brings us new chances to defeat DDoS attacks in cloud computing environments. Nevertheless, there is a contradictory relationship between SDN and DDoS attacks. On one hand, the capabilities of SDN, including software-based traffic analysis, centralized control, global view of the network, dynamic updating of forwarding rules, make it easier to detect and react to DDoS attacks. On the other hand, the security of SDN itself remains to be addressed, and potential DDoS vulnerabilities exist across SDN platforms. In this paper, we discuss the new trends and characteristics of DDoS attacks in cloud computing, and provide a comprehensive survey of defense mechanisms against DDoS attacks using SDN. In addition, we review the studies about launching DDoS attacks on SDN, as well as the methods against DDoS attacks in SDN. To the best of our knowledge, the contradictory relationship between SDN and DDoS attacks has not been well addressed in previous works. This work can help to understand how to make full use of SDN's advantages to defeat DDoS attacks in cloud computing environments and how to prevent SDN itself from becoming a victim of DDoS attacks, which are important for the smooth evolution of SDN-based cloud without the distraction of DDoS attacks.

Software-Defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: A Survey, Some Research Issues, and Challenges

Mobile edge computing has risen as a promising technology for augmenting the computational capabilities of mobile devices Meanwhile, in-network caching has become a natural trend of the solution of handling exponentially increasing Internet traffic The important issues in these two networking paradigms are computation offloading and content caching strategies, respectively In order to jointly tackle these issues in wireless cellular networks with mobile edge computing, we formulate the computation offloading decision, resource allocation and content caching strategy as an optimization problem, considering the total revenue of the network Furthermore, we transform the original problem into a convex problem and then decompose it in order to solve it in a distributed and efficient way Finally, with recent advances in distributed convex optimization, we develop an alternating direction method of multipliers-based algorithm to solve the optimization problem The effectiveness of the proposed scheme is demonstrated by simulation results with different system parameters

Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing

Edge Computing provides mobile and Internet-of-Things (IoT) app vendors with a new distributed computing paradigm which allows an app vendor to deploy its app at hired edge servers distributed near app users at the edge of the cloud. This way, app users can be allocated to hired edge servers nearby to minimize network latency and energy consumption. A cost-effective edge user allocation (EUA) requires maximum app users to be served with minimum overall system cost. Finding a centralized optimal solution to this EUA problem is NP-hard. Thus, we propose EUAGame, a game-theoretic approach that formulates the EUA problem as a potential game. We analyze the game and show that it admits a Nash equilibrium. Then, we design a novel decentralized algorithm for finding a Nash equilibrium in the game as a solution to the EUA problem. The performance of this algorithm is theoretically analyzed and experimentally evaluated. The results show that the EUA problem can be solved effectively and efficiently.

A Game-Theoretical Approach for User Allocation in Edge Computing Environment

Recently, software defined networks (SDNs) and cloud computing have been widely adopted by researchers and industry. However, widespread acceptance of these novel networking paradigms has been hampered by the security threats. Advances in the processing technologies have helped attackers in increasing the attacks too, for instance, the development of Denial of Service (DoS) attacks to distributed DoS (DDoS) attacks which are seldom identified by conventional firewalls. In this paper, we present the state of art of the DDoS attacks in SDN and cloud computing scenarios. Especially, we focus on the analysis of SDN and cloud computing architecture. Besides, we also overview the research works and open problems in identifying and tackling the DDoS attacks.

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A Survey on Distributed Denial of Service (DDoS) Attacks in SDN and Cloud Computing Environments

Accompanied by the rapid development of mobile video service requirements, the dramatic increase in video streaming traffic causes a heavy burden for mobile networks. Mobile edge computing (MEC) has become a promising paradigm to enhance the mobile networks by providing cloud-computing capabilities within the radio access network (RAN). With the ability of content caching and context awareness, MEC could provide low-latency and adaptive-bitrate video streaming to improve service providing ability of the RAN. In this paper, we propose an MEC enhanced adaptive bitrate (ABR) video delivery scheme, which combines content caching and ABR streaming technology together. The MEC server acts as a controlling component to implement the video caching strategy and adjust the transmitted bitrate version of videos flexibly. A Stackelberg game is formulated to deal with the storage resources occupied by each base station. The joint cache and radio resource allocation (JCRA) is tackled into a matching problem. We propose the JCRA algorithm to solve the matching problem in order to make the cooperation between cache and radio resources. Simulation results reveal that the proposed scheme could improve both the cache hit ratio and the system throughput over other schemes.

Mobile Edge Computing Enhanced Adaptive Bitrate Video Delivery With Joint Cache and Radio Resource Allocation

In mobile cloud computing systems, cloud computing has a significant impact on wireless networks Cloud computing and wireless networks have traditionally been addressed separately in the literature In this paper, we jointly study the operations of cloud computing and wireless networks in mobile computing environments, where the objective is to improve the end-to-end performances of cloud mobile media delivered through mobile cloud computing systems Unlike most existing studies on wireless networks, where only the spectrum efficiency is considered, we consider not only the spectrum efficiency in wireless networks but also the pricing information in the cloud, based on which power allocation and interference management in the wireless networks are performed We formulate the problems encountered in the operations of mobile cloud computing environments, including determining the price to charge for media services, resource allocation, and interference management, as a Stackelberg game model Moreover, we extend this game model with multiple players through network virtualization technology, and adopt the replicator dynamics method to solve the evolutionary game between the different groups of small cells Furthermore, a backward induction method is used to analyze the proposed Stackelberg game Simulation results are presented to show the effectiveness of the proposed techniques

Anumula Satheesh

Papers

Joint Cloud and Wireless Networks Operations in Mobile Cloud Computing Environments With Telecom Operator Cloud