Shan-Hsiang Shen

2L-MAC: A MAC Protocol with Two-Layer Interference Mitigation in Wireless Body Area Networks for Medical Applications

This paper investigates the issue of interference mitigation in wireless body area networks (BANs). Although several approaches have been proposed in BAN standard IEEE 802.15.6, they increase transmission latency or energy cost, and do not mitigate interference effectively. In order to avoid both intra- and inter-BAN interference, we present a MAC protocol with two-layer interference mitigation (2L-MAC) for BANs. Considering the QoS requirements of BANs, the proposed protocol not only avoids packet collisions but also reduces transmission delay and energy consumption in sensors. Moreover, channel switching is triggered whenever a BAN needs to acquire more bandwidth. Simulation results show that our protocol outperforms other protocols in terms of delivery rate, latency and energy saving.

Reliable multicast routing for software-defined networks

Current traffic engineering in SDN mostly focuses on unicast. By contrast, compared with individual unicast, multicast can effectively reduce network resources consumption to serve multiple clients jointly. Since many important applications require reliable transmissions, it is envisaged that reliable multicast plays a crucial role when an SDN operator plans to provide multicast services. However, the shortest-path tree (SPT) adopted in current Internet is not bandwidth-efficient, while the Steiner tree (ST) in Graph Theory is not designed to support reliable transmissions since the selection of recovery nodes is not examined. In this paper, therefore, we propose a new reliable multicast tree for SDN, named Recover-aware Steiner Tree (RST). The goal of RST is to minimize both tree and recovery costs, while finding an RST is very challenging. We prove that the RST problem is NP-Hard and inapproximable within k, which is the number of destination nodes. Thus, we design an approximate algorithm, called Recover Aware Edge Reduction Algorithm (RAERA), to solve the problem. The simulation results on real networks and large synthetic networks, together with the experiment on our SDN testbed with real YouTube traffic, all manifest that RST outperforms both SPT and ST. Also, the implementation of RAERA in SDN controllers shows that an RST can be returned within a few seconds and thereby is practical for SDN networks.

REfactor-ing content overhearing to improve wireless performance

Many systems have leveraged the broadcast nature of wireless radios to improve wireless capacity and performance. While conventional approaches have focused on overhearing entire packets, recent designs have argued that focusing on overheard content may be more effective. Unfortunately, key design choices in these approaches limit them from fully leveraging the benefits of overhearing content. We propose a cleaner refactoring of functionality where-in overhearing is realized at the sub-packet payload level through the use of IP-layer redundancy elimination. We show that this dramatically improves the effectiveness of prior overhearing based approaches and enables new designs, e.g., enhanced network coding, where content overhearing can be more effectively integrated to improve performance. Realizing the benefits of IP-layer content overhearing requires us to overcome challenges arising from the probabilistic nature of wireless reception (which could lead to inconsistent state) and the limited resources on wireless devices. We overcome these challenges through careful data structure and wireless redundancy elimination designs. We evaluate the effectiveness of our system using experimentation on real traces. We find that our design is highly effective: e.g., it can improve goodput by nearly 25% and air time utilization by nearly 20%.

Multicast traffic engineering for software-defined networks

Although Software-Defined Networking (SDN) enables flexible network resource allocations for traffic engineering, current literature mostly focuses on unicast communications. Compared to traffic engineering for multiple unicast flows, multicast traffic engineering for multiple trees is very challenging not only because minimizing the bandwidth consumption of a single multicast tree by solving the Steiner tree problem is already NP-Hard, but the Steiner tree problem does not consider the link capacity constraint for multicast flows and node capacity constraint to store the forwarding entries in Group Table of OpenFlow. In this paper, therefore, we first study the hardness results of scalable multicast traffic engineering in SDN. We prove that scalable multicast traffic engineering with only the node capacity constraint is NP-Hard and not approximable within δ, which is the number of destinations in the largest multicast group. We then prove that scalable multicast traffic engineering with both the node and link capacity constraints is NP-Hard and not approximable within any ratio. To solve the problem, we design a δ-approximation algorithm, named Multi-Tree Routing and State Assignment Algorithm (MTRSA), for the first case and extend it to the general multicast traffic engineering problem. The simulation and implementation results demonstrate that the solutions obtained by the proposed algorithm outperform the shortest-path trees and Steiner trees. Most importantly, MTRSA is computation-efficient and can be deployed in SDN since it can generate the solution with numerous trees in a short time.

Service chain embedding with maximum flow in software defined network and application to the next-generation cellular network architecture

With software-defined network (SDN) and network function virtualization (NFV) techniques, we can embed the service chain consisting of a sequence of virtualized network functions (VNFs), i.e., we can determine the flow path and deploy the VNFs contained in the service chain at any place on the path. In the literature, the methods of service chain embedding bound the number of VNFs at a node, whereas the link capacities are disregarded and the amount of flows is not considered, which could cause serious congestion. In addition, according to our experiment, the process overhead on a computation node is linear to the total amount of flows processed. In this paper, we propose a method of service chain embedding to maximize the total amount of flows while bounding the process overhead of the flows on a node by its computation capability and the total amount of flows on an link by its bandwidth capacity. To our knowledge, our method is the first approximation algorithm of service chain embedding with considering flow in the literature. Simulations show our algorithm has good performance in terms of the total amount of flows.

Privacy-preserving deep packet filtering over encrypted traffic in software-defined networks

Deep packet filtering (DPF) has been demonstrated as an essential technique for effective fine-grained access controls, but it is commonly recognized that the technique may invade the individual privacy of the users. Secure computation can address the tradeoff between privacy and DPF functionality, but the current solutions limit the scalability of the network due to the intensive computation overheads and large connection setup delay, especially for the latest network paradigm, network function virtualisation (NFV) and software-defined network (SDN). In this paper, therefore, we propose a privacy-preserving deep packet filtering protocol, named DPF-ET, that can efficiently perform filtering function over encrypted traffic while diminishing the communication overhead and setup delay for the controller in SDN. DPF-ET guarantees the data privacy for users and remains rule privacy for the network owner. The implementation results on an experimental HP SDN/NFV platform demonstrate that the proposed DPF-ET outperforms the current approaches by reducing 250 times in the communications overhead and 32 times in the setup delay.

DECOR: a distributed coordinated resource monitoring system

Network resources are often limited, so how to use them efficiently is an issue that arises in many important scenarios. Many recent proposals rely on a central controller to carefully orchestrate resources across multiple network locations. The central controller gathers network information and relative levels of usage of different resources and calculates optimized task allocation arrangements to maximize some global benefit. Examples of architectures that use this framework include coordinated sampling (cSamp [1]) and redundancy elimination (SmartRE [2]). However, a centralized solution creates practical problems as it is susceptible to overload, and the controller is a single point of failure. In this paper, we present a distributed solution called decor that achieves global optimization based on local information that closes to centralized approaches in terms of performance. In decor, the responsibility of resource monitoring and information gathering is spread among multiple nodes; thus, no single point is overloaded. Allocation of tasks is also done in a similar distributed fashion. decor can easily scale up to large networks, and the partial network failures do not affect DECORs functioning in other parts of the network. decor can be applied to most of path-based applications. We describe in detail how to apply it to distributed SmartRE and implement it in the Click software router.

Service Overlay Forest Embedding for Software-Defined Cloud Networks

Network Function Virtualization (NFV) on Software-Defined Networks (SDN) can effectively optimize the allocation of Virtual Network Functions (VNFs) and the routing of network flows simultaneously. Nevertheless, most previous studies on NFV focus on unicast service chains and thereby are not scalable to support a large number of destinations in multicast. On the other hand, the allocation of VNFs has not been supported in the current SDN multicast routing algorithms. In this paper, therefore, we make the first attempt to tackle a new challenging problem for finding a service forest with multiple service trees, where each tree contains multiple VNFs required by each destination. Specifically, we formulate a new optimization, named Service Overlay Forest (SOF), to minimize the total cost of all allocated VNFs and all multicast trees in the forest. We design a new 3ρST-approximation algorithm to solve the problem, where ρST denotes the best approximation ratio of the Steiner Tree problem, and the distributed implementation of the algorithm is also presented. Simulation results on real networks for data centers manifest that the proposed algorithm outperforms the existing ones by over 25%. Moreover, the implementation of an experimental SDN with HP OpenFlow switches indicates that SOF can significantly improve the QoE of the Youtube service.