Bing Leng

A mechanism for reducing flow tables in software defined network

The software defined network (SDN) has been developing tremendously in recent years. Numerous studies are proposed on the performance of SDN in academia. The idea of programmable network which is the foundation of SDN ensures dynamic network management by separating the control plane away from the network switches. The focus of this paper is the flow tables size in OpenFlow switches which is a significant bottleneck in SDNs practical application. We propose a mechanism named “Flow Table Reduction Scheme”(FTRS) for reducing the flow table size and maintaining the omnipotent controllers functions at the same time. We test the performance of FTRS both in simulation and experiment and the results show that FTRS is able to reduce 98% at most of the size of flow table with no impact on networks normal functions.

High-throughput anycast routing and congestion-free reconfiguration for SDNs

In this work, we focus on designing high-throughput anycast mechanisms in a software Defined Network (SDN), as anycast routing serves as a fundamental building block for many services. Specifically, we investigate two main challenges for efficient implementation of a SDN-based anycast system: high throughput anycast routing (HTAR) and congestion-free anycast reconfiguration (CFAR). For the first challenge, we design an anycast routing (ARFU) algorithm, based on the fully polynomial time approximation scheme and the single-source unsplittable flow routing method. We prove that ARFU produces a route that can achieve a throughput at least 1/2(1+ξ) of the optimum, where ξ > 0 is an arbitrarily small constant. We then propose an anycast reconfiguration algorithm with transitive configurations, called ARTC, for congestion-free. This algorithm tries to find a routing reconfiguration procedure consisting of at most T ≥ 1 transitive configurations while meeting all the flow demands. When traffic demands can not be satisfied, ARTC maximizes the minimum throughput using one transitive configuration. Our simulations demonstrate high-efficiency of our algorithms.

Joint channel and sink assignment for data collection in cognitive wireless sensor networks

Summary Data collection is a fundamental operation in cognitive wireless sensor networks (CWSNs). However, previous works on data collection assume that a node can transmit data to any node within its transmission range, which is not reasonable in CWSNs. To ensure that the previous works can be applied in CWSNs, this paper focuses on the joint channel and sink assignment problem, which is a critical preparatory work for data collection in CWSNs. Because the capacity performance of a CWSN is usually considered as a key problem in fundamental understanding, we are interested in finding a joint channel and sink assignment for each sensor node, such that the minimum capacity of all sensor nodes is maximized. We formulate our problem as a mixed integer linear program by some elaborate mathematical skills. Then, two algorithms based on greedy strategy and linear relaxation technique are proposed. Extensive simulations results show that our algorithms are efficient and able to achieve near-optimal performance. Copyright

FTRS: A mechanism for reducing flow table entries in software defined networks

Abstract A flow table in an OpenFlow based switch is used to not only operate the switch, but also carry out the control function of the Software Defined Network (SDN) controller. However, as a core participant of network management, its limited storage has been a significant roadblock for the industrialization of SDN. It is a significant problem to reduce the number of flow entries needed in the almost full-filled flow tables, and at the same time, to retain the original QoS as much as possible — or known as the “Flow Table Congestion Problem” (FTCP) . We propose a mechanism called “Flow Table Reduction Scheme” (FTRS) to efficiently solve FTCP and evaluate the performance of FTRS both via simulation and experiment. The results show that FTRS is able to reduce the number of flow entries by 98% at most of the size of flow table with no influence on network’s normal functions.

Optimizing virtual machine placement in distributed clouds with M/M/1 servers

As more and more applications migrate into clouds, the placement of virtual machines for these applications has a significant impact on the performance of cloud systems. A number of virtual machine (VM) placement techniques have been proposed over recent years. However, most of the existing works on VM placement ignore the response latency of the requests from tenants. In this paper, we investigate the techniques of VM placement in distributed clouds with stochastic requests from the tenants. We first model the requests for each application from the corresponding tenant as independent Poisson stream. Moreover, based on the analyses of distributed cloud resources, the VMs with their data nodes are modeled as simple M/M/1 queueing systems. Then, we propose the problems of VM placement with two distinct optimization objectives. For each objective, we present the formal definition and prove its NP-hardness. To deal with them, we propose some algorithms and the performances of them are analysed in each section. For applying to the situation of lacking of resource, we propose two extended algorithms. We conduct abundant simulation experiments in distributed cloud environment to evaluate the performance of our proposed algorithms. The simulation results show that the proposed algorithms can significantly improve the performance of their corresponding objectives.

(Invited) popularity-based content replication scheme for wireless mesh network

Wireless Mesh Network (WMN) is now being extensively used as a cost-effective means for coverage extension and backhaul relaying. One of the key challenges it suffers from is data access efficiency arising from resource constraints of wireless communications. Therefore, many content replication schemes based on the popularity of objects have been proposed for WMNs. However, most of the existing works on object replication schemes in WMNs ignore the restricted service rate of the replica servers. In this paper, we investigate the techniques of popularity-based content replication in WMNs to optimize the overall performance of average latency. We define the popularity of objects and model the replica server as simple M/M/1 queuing systems. Then, a formal definition and formalization of the popularity-based replication problem will be given. We show this problem is NP-complete and propose a distributed scheme composed of two-phase. We conduct abundant simulation experiments to evaluate the performance of our proposed scheme. The simulation results show that the proposed scheme gains much lower average latency without increasing the network load.

Replica placement in content delivery networks with stochastic demands and M/M/1 servers

Content Delivery Network (CDN) is proposed for replicating data objects at multiple locations in the network and encounters vast potential for future development, as a result of which, a number of replica placement techniques have been proposed over the last decade. However, most of the existing works on replica placement (RP) ignore the statistical property of the demands and the restricted service rate of the servers. In this paper, we investigate the techniques of replica placement in CDNs with stochastic demands and M/M/1 servers to optimize the overall performance in the network. We first model the demands and the servers as independent Poisson streams and simple M/M/1 queueing systems, respectively. Then, a formal definition and formalization of RP problem will be given. We show that RP problem is NP-complete and propose two heuristic algorithms: Greedy Dropping (GD) and Tabu Search (TS). We conduct abundant simulation experiments to evaluate the performance of our proposed algorithms. According to our simulation results, both of the two algorithms are efficient in finding a feasible solution with high probability. Especially, the TS decreases the average delay of the demands about 50% on average.

Urban Traffic Condition Estimation: Let WiFi Do It

Surface transportation is of a great importance in urban life. Fueled by the promise of Smart City, it is becoming more and more common to provide WiFi services in urban Public Transportation System (PTS). In this paper, we present a practical method to make use of the WiFi service provided on buses to estimate real-time urban traffic condition. We validate the proposed method in a city district and show that it is an excellent alternative or supplement of the existing traffic condition estimation services.

A decision-tree-based on-line flow table compressing method in Software Defined Networks

It is a common view in Software Defined Network (SDN) that the flow table plays the most significant role in SDN architecture, but suffers from the limited TCAM chips. The shortage of flow table storage strongly impacts the quality of service (QoS) provided by SDN, but requires rational solutions. In this paper, we present a practical on-line approach based on the decision tree structure to solve this problem. Our performance is evaluated by the comparison with other existing technologies.

A self-adaptive reconfiguration scheme for throughput maximization in municipal WMNs

Wireless mesh networks (WMNs) are being used and deployed widely all around the world for various reasons such as public safety, environmental monitoring and city-wide wireless Internet services [4], [12]. Although faced with some difficulties, wireless mesh network is thought to be a preferred municipal Internet service provider [5] with huge potential due to its automatic connection, ease of installation, dynamic route discovery, flexibility and other advantages. Since plenty of cities such as Singapore and the city of Cambridge have put providing ubiquitous Internet access on the agenda [3], the research on providing QoS-guaranteed municipal WMNs is in urgent need.