SDN-Enabled Game-Aware Routing for Cloud Gaming Datacenter Network

In this paper, we study the problem of how to dispatch the play requests to the cloud servers in a cloud gaming system. We show that the dispatching strategy of play requests may heavily affect the total service cost of the cloud gaming system. The play request dispatching problem can be considered as a variant of the dynamic bin packing problem. However, we show that the classical bin packing algorithms such as First Fit and Best Fit are not efficient in dispatching the play requests in cloud gaming due to the diurnal workload pattern of online games. To address this issue, we propose an efficient request dispatching algorithm that assigns the play requests according to the predicted ending times of the game sessions. Through extensive evaluations using real online gaming traces, we show that the proposed dispatching algorithm can significantly reduce the resource waste of the cloud servers and thus decrease the total service cost compared to the First Fit and Best Fit algorithms.

In Data Center facilities, network performance is crucial. The system performance requirements are usually high throughput and packet loss sensitive. In addition, the data center also requires redundant links, in order to avoid the occurrence of failure in the network. Applying topologies such as as fat-tree can solve the redundant link needs problem. However, the use of redundant links that are only used as backups are considered ineffective. A routing mechanism that can exploit the potential of existing links sufficiently is required. Equal-cost multipath routing (ECMP) is a routing scheme that can be implemented to solve the problem. With the implementation of software defined network (SDN) on the network, the construction of this routing scheme will be more accessible. The ECMP scheme utilizes modified Dijkstra's algorithm to search for the shortest path, and uses the modulo-n hashing method in the selection of the delivery path. This paper implements ECMP scheme on fat-tree topology with SDN-based network. The results obtained in this study prove that the network implementing ECMP can provide a throughput difference of 60.14Mbps when compared with static routing in a 20Mbps bandwidth traffic test scenario. Also the ECMP network can provide 15.72% less packet loss compared to static routing networks.

The emerging Cloud Gaming Service provides a highly accessible video gaming experience. With Cloud Gaming, potential players without enough local resource can access high-quality gaming using low-spec devices. With advancing technology, we consider that if the processing power at low-spec devices can be well harvested, the quality delivered on Cloud Gaming can be further improved. Therefore, we propose a Hybrid-Streaming System that aimed at improving the graphic quality delivered by Cloud Gaming. By utilizing the available rendering power from both the Cloud Server and client PC, the system distributes rendering operations to both sides to achieve the desired improvement. Quantitative results show the proposed method improves graphics quality, as well as reducing the server’s workload while attaining acceptable network bandwidth consumption levels.

Software-Defined Networking (SDN) is now a well-established approach in 5G, Internet of Things (IoT) and Cloud Computing. The primary idea behind its immense popularity is the separation of its underlying intelligence from the data-carrying components like routers and switches. The intelligence of the SDN-based networks lies in the central point, popularly known as the SDN controller. It is the central control hub of the SDN-based network, which has full privileges and a global view over the entire network. Providing security to SDN controllers is one such important task. Whenever one wishes to implement SDN into their data center or network, they are required to provide the website to SDN controllers. Several attacks are becoming a hurdle in the exponential growth of SDN, and among all one such attack is a Distributed Denial of Service (DDoS) attack. In a couple of years, several new SDN controllers will be available. Among many, Open Networking Operating System (ONOS) and OpenDayLight (ODL) are two popular SDN controllers laying the foundation for many other controllers. These SDN controllers are now being used by numerous businesses, including Cisco, Juniper, IBM, Google, etc. In this paper, vulnerability analysis is carried out against DDoS attacks on the latest released versions of both ODL and ONOS SDN controllers in real-time cloud data centers. For this, we have considered distributed SDN controllers (located at different locations) on two different clouds (AWS and Azure). These controllers are connected through the Internet and work on different networks. DDoS attacks are bombarded on the distributed SDN controllers, and vulnerability is analyzed. It was observed with experimentation that, under five different scenarios (malicious traffic generated), ODL-3 node cluster controller had performed better than ONOS. In these five different scenarios, the amount of malicious traffic was incregradually increased. It also observed that, in terms of disk utilization, memory utilization, and CPU utilization, the ODL 3-node cluster was way ahead of the SDN controller.

With the increasing popularity of Massively Multiplayer Online Game (MMOG) and fast growth of mobile gaming, cloud gaming exhibits great promises over the conventional MMOG gaming model as it frees players from the requirement of hardware and game installation on their local computers. However, as the graphics rendering is offloaded to the cloud, the data transmission between the end-users and the cloud significantly increases the response latency and limits the user coverage, thus preventing cloud gaming to achieve high user Quality of Experience (QoE). To solve this problem, previous research suggested deploying more data centers, but it comes at a prohibitive cost. We propose a lightweight system called Cloud Fog, which incorporates "fog" consisting of super nodes that are responsible for rendering game videos and streaming them to their nearby players. Fog enables the cloud to be only responsible for the intensive game state computation and sending update information to super nodes, which significantly reduce the traffic hence the latency and bandwidth consumption. Experimental results from PeerSim and Planet Lab show the effectiveness and efficiency of Cloud Fog in increasing user coverage, reducing response latency and bandwidth consumption.

Today, there is a generalized standard usage of internet for all.The devices via multiple technologies that facilitates to provide few communication methods to scholars to work with. By forming multiple paths in the data center network, latest generation data centers offer maximum bandwidth with robustness. To utilize this bandwidth, it is necessary that different data flows take separate paths. In brief, a single-path transport seems inappropriate for such networks. By using Multipath TCP, we must reconsider data center networks, with a diverse approach as to the association between topology, transport protocols, routing. Multipath TCP allows certain topologies that single path TCP cannot use. In newer generation data centers, Multipath TCP is already deployable using extensively deployed technologies such as Equal-cost multipath routing. But, major benefits will come when data centers are specifically designed for multipath transports. Due to manifold of technologies like Cloud computing, social networking, and information networks there is a need to deploy the number of large data centers. While Transport Control Protocol is the leading Layer-3 transport protocol in data center networks, the operating conditions like high bandwidth, small-buffered switches, and traffic patterns causes poor performance of TCP. Data Center TCP algorithm has newly been anticipated as a TCP option for data centers which address these limitations. It is worth noting that traditional TCP protocol.

Software Defined Networking (SDN) is a rapidly emerging technology in the commercial market, and is a technology that should be embraced by the defence and emergency services to enable more flexible and adaptable communication networks in the future. Common deployment of SDN, especially in data centres, involves building a separate network for the control channel between forwarding devices and the SDN controllers. For geographically distributed networks typically found in defence and emergency services, it is often not feasible to establish a separate dedicated network for the control channel. In such networks, traffic between SDN controllers and forwarding devices therefore needs to be in-band in the same network that the SDN controllers should control. This paper describes the steps necessary for forwarding devices to both discover and set up the connections with SDN controllers when in-band control channels must be used. The work expands on earlier published work on setting up in-band control channels between SDN controllers and the forwarding devices. Especially, our solution that uses the Intent frameworks of major SDN controllers improves on network resilience in disconnected, intermittent and limited networks and the solution will allow for implementation of enhanced security mechanisms compared to previous work.

Cloud gaming is a recent approach to gaming, where processing for the games occurs on well-equipped servers within the cloud and a video stream is returned to the user, meaning users can play high-end games on devices that lack computational power. Different games require different amounts of computational resources and computation times. It would be desirable to efficiently pack a number of servers with multiple games at once, however this is complicated within a geo-distributed cloud system as we must consider that not every data center can fulfil every game request due to latency requirements. Within this work, we present shadow routing algorithms to distribute game requests to cloud data centers and also to pack the servers within the data centers with these game requests. These algorithms are designed to operate in order to minimize total cost from server hire and bandwidth usage, and we prove their performance is asymptotically close to optimal. An experiment using realistic arrival rates is given, and the results verify our theory within a realistic context. Also shown using proof and experimentation is that the algorithms can adapt themselves to periodic changes as demand raises and falls while remaining close to the optimal, which is a particular weak point of other schemes.

Cloud gaming is a multi-billion dollar industry. A client in cloud gaming sends its movement to the game server on the Internet, which renders and transmits the resulting video back. In order to provide a good gaming experience, a latency below 80 ms is required. This means that video rendering, encoding, transmission, decoding, and displaying have to finish within that time frame, which is especially challenging to achieve due to server overload, network congestion, and losses. In this paper, we propose VIGOR, a new method to revive cloud gaming sessions by recovering lost or corrupted video frames. Unlike traditional video frame recovery, VIGOR uses game states to enhance recovery accuracy significantly and utilizes partially decoded frames to recover lost portions. We develop a holistic system that consists of (i) efficiently extracting game states, (ii) modifying H.264 video decoder to generate a mask to indicate which portions of video frames need recovery, and (iii) designing a novel neural network to recover either complete or partial video frames. VIGOR is extensively evaluated using iPhone 12 and laptop implementations, and we demonstrate the utility of game states in the game video recovery and the effectiveness of our overall design.

Live Virtual Machine (VM) migration has significantly improved the flexibility of modern Data Centers (DC). However, seamless live migration of a VM between geo-distributed DCs faces several challenges due to difficulties in preserving the network configuration after the migration paired with a large network convergence time. Although SDN-based approaches can speed up network convergence time, these techniques have two limitations. First, they typically react to the new topology by installing new flow rules once the migration is finished. Second, because the WAN is typically not under SDN control, they result in sub-optimal routing thus severely degrading the network performance once the VM is attached at the new location. In this paper, we identify networking challenges for VM migration across geo-distributed DCs. Based on those observations, we design a novel long-haul VM migration scheme that overcomes those limitations. First, instead of reactively restoring connectivity after the migration, our SDN-based approach proactively restores flows across the WAN towards the new location with the help of EVPN and VXLAN overlay technologies. Second, the SDN controller accelerates the network convergence by announcing the migration to other controllers using MP-BGP control plane messages. Finally, the SDN controller resolves the sub-optimal routing problem that arises as a result of migration implementing a distributed anycast gateway. We implement our approach as extensions to the OpenDaylight controller. Our evaluation shows that our approach outperforms existing approaches in reducing the downtime by 400 ms and increasing the application performance up to 12 times.

The proliferation of cloud computing has forced data centers to support a large number of dynamic resources such as virtual machines and storage volumes from any physical location within the data center. This has led to highly volatile and unpredictable traffic patterns. The emergence of cloud applications that exchange large volumes of information have created large persistent flows that need to coexist with other types of traffic. As a result, a number of data center topologies have been proposed to support cloud applications. One of the topologies that has gained prominence is the Clos network. On one hand, Clos networks provide many nice properties, such as equidistant hops, bandwidth, and latency. On the other hand the routing of diverse traffic flows still remains an issue. Current routing methods such as equal-cost multi-path (ECMP) routing that rely on flow hashing over equal cost paths do not take into consideration traffic volume nor network state. In this paper, we investigate routing in Clos topologies. We formulate optimal flow routing in Clos networks as a binary multicommodity flow problem and present optimized flow re-routing, a modified version of the binary multicommodity flow problem that uses a heuristics approach to minimize hash collisions. We also propose FlowFit, a practical optimization method that uses network state to optimally re-assign flows to links. Our experimental and simulation results show a significant improvement in bisection bandwidth and flow completion time over ECMP.

Various applications in a multi-tenant architecture based cloud computing comprises various requirements and priorities. Severe failure of a critical application may result if the network is congested in a data center. Hence, it is an important to use an efficient resource provisioning technique for ensuring transfer of high priority data to the other traffics still when the network is congested. Therefore, a new framework of Home Cloud architecture is proposed in this paper to provide an effective and flexible delivery of new applications in an edge-cloud architecture which integrates the two complementary technologies of Software-Defined Networking (SDN) and Network Function Virtualization (NFV). In SDN infrastructure, this presents a priority aware resource placement algorithms by taking into consideration of both host and network resources. The Virtual Machines (VMs) of high priority applications are placed at the strongly connected hosts by introducing the priority aware VM allocation (PAVA) algorithm for reducing the possibility of causing network congestion by other tenants. It also guarantees the critical applications for a required bandwidth by means of allocating bandwidth through the setting of priority queues for each network connection within the network of data center handled by SDN controller. The simulation result of the proposed system shows that the combination of proposed approaches will allocate sufficient resources for high-priority applications within a Home Cloud data centre to meet the QoS requirements.

Contrary to conventional gaming-on-demand services that stream gaming video from cloud to players' terminals, a decomposed cloud gaming platform supports flexible migrations of gaming components between the cloud server and the players' terminals. In this paper, we present the design and implementation of the proposed decomposed gaming system. The cognitive resource optimization of the system under distinct targets, including the minimization of cloud, network, and terminal resources and response delay, subject to quality of service (QoS) assurance, is formulated as a graph partitioning problem that is solved by exhaustive searches. Simulations and experimental results demonstrate the feasibility of cognitive resource management in a cloud gaming system to efficiently adapt to variations in the service environments, such as increasing the number of supported devices and reducing the network bandwidth consumption of user terminals, while satisfying different QoS requirements for gaming sessions. We also suggest two heuristic algorithms based on local greedy and genetic algorithm approaches, which can potentially provide scalable but suboptimal solutions in large-scale implementations.

Software defined networking (SDN) is the centralised network management technology that could reduce the network administration and policy enforcement overhead in the traditional IP networking. SDN controller is the network operating system responsible for entire network operations. However, there are many open source controllers available, such as NOX, POX, FloodLight and OpenDaylight. Each controller has its own properties that could support specific requirements. In this paper, we have compared the performance of most familiar OpenFlow controllers like NOX, POX, Ryu, FloodLight and OpenFlow reference controller based on their packet handling capacity, by varying the packet size, number of packets and arrival pattern in the IP traffic flows. Distributed internet traffic flow generator (D-ITG) tool has been used to measure the performance in terms of delay, jitter, throughput and packet loss. Our experimentation results show that, FloodLight has the better throughput and less delay when compared to other controllers. This work substantiates the researcher in choosing the appropriate controller for their requirements.

Cloud computing is one among the emerging platforms in business, IT enterprise and mobile computing applications. Resources like Software, CPU, Memory and I/O devices etc. are utilized and charged as per the usage, instead of buying it. A Proper and efficient resource allocation in this dynamic cloud environment becomes the challenging task due to drastic increment in cloud usage. Various promising technologies have been developed to improve the efficiency of resource allocation process. But still there is some incompetency in terms of task scheduling and power consumption, when the system gets overloaded. So an energy efficient task scheduling algorithm is required to improve the efficiency of resource allocation process. In this paper an improved task scheduling and an optimal power minimization approach is proposed for efficient dynamic resource allocation process. Using prediction mechanism and dynamic resource table updating algorithm, efficiency of resource allocation in terms of task completion and response time is achieved. This framework brings an efficient result in terms of power reduction since it reduces the power consumption in data centers. The proposed approach gives accurate values for updating resource table. An efficient resource allocation is achieved by an improved task scheduling technique and reduced power consumption approach. The Simulation result gives 8% better results when comparing to other existing methods.