Unmanned aerial vehicle (UAV) has been an emerging technology used for various applications. Enabling wireless base station (e.g., Wi-Fi AP) on UAV can be one of promising UAV applications. In this work, we focus on a performance fairness issue on ground Wi-Fi users and aim to maximize the minimum throughput performance among them. To this end, we propose a solution, designated UAV-FAP (UAV with user Fairness-driven AP), to drive UAV-AP to reach a location that can offer max-min throughput performance. It employs a heuristic-based hierarchical search method to search for the target location efficiently. By conducting experiments on a real UAV-AP platform, we first study the issues of antenna pointing direction and vertical/horizontal UAV-AP placement, and then collect Wi-Fi throughput statistics for a trace-driven simulator in the evaluation. The evaluation result shows that UAV-FAP can outperform the default case, where the UAV-AP stays at the center of a serving area, by 2.0%-21.5% throughput gains; in some cases, it takes as small as only 7% of the moving distance needed by a fine-grained exhaustive search to reach target max-min locations.

Real-time control solutions for unmanned aerial vehicles (UAVs) have attracted great interest in recent years. Most existing control methods use Wi-Fi technology. While Wi-Fi is inexpensive and easy to use, it has only a limited transmission range. Thus, 4G/5G cellular networks have been proposed as an alternative enabling technology. This study focuses on the problem of improving the appropriateness of the control commands sent by the ground control station (GCS) to the UAV over the control and nonpayload communication (CNPC) link of the UAV through the cellular network. To satisfy the low-latency requirement of the CNPC link, multiaccess edge computing (MEC) technology is leveraged to collocate the GCS and base station. The effectiveness of the proposed edge-based approach is demonstrated by conducting experiments on two LTE platforms with different MEC deployment methods. An edge-enabled UAV control solution is proposed in which each end-to-end control delay in the UAV-GCS system is estimated based on the preceding delay such that the location of the UAV at the moment it receives the control command from the GCS can be predicted in advance and taken into consideration by the GCS when formulating an appropriate control decision. To this end, an analytical modeling method is proposed for estimating the expected error range of each control delay based on a bimodal distribution approximation of the empirical control delays observed at the UAV. Finally, an event-driven simulator is developed to confirm the accuracy of the analytical predictions of the control delay based on the expected error between consecutive delays.

Unmanned aerial vehicles (UAVs) are being investigated to substitute for labor in many indoor applications, e.g., asset tracking and surveillance, where the global positioning system (GPS) is not available. Also, emerging autonomous UAVs are expected to land in indoor parking aprons automatically. Such GPS-denied environments require alternative non-GPS positioning methods. Although there have been some vision-based solutions for UAVs, they perform poorly in the scenes with bad illumination conditions or estimate only relative locations but not global positions. Other common indoor localization methods do not cover UAV factors, such as low power and flying behaviors. To this end, we propose a practical non-GPS positioning system for UAVs, named WBF-PS (WiGig Beam Fingerprinting based Positioning System), using low-power, off-the-shelf WiGig devices. We formulate a 3-dimensional beam fingerprint for the positioning by leveraging the diversity of available transmitter/receiver beams and the link quality. To augment the positioning accuracy, we not only use a weighted k-nearest neighbors algorithm to overcome partial fingerprint inaccuracy but also apply the particle filtering technique into considering the UAV motion. We prototype and evaluate WBF-PS on a UAV platform. The result shows that the positioning errors at the 90th percentile are below 1 m in various cases.

The multi-controller architecture is a must to improve scalability and reliability of software defined networks (SDNs). A hierarchical multi-controller architecture allows a global controller to handle rare events, such as routing events from local controllers. A failover mechanism, which includes failure detection and recovery, is necessary for the multi-controller architecture in case of a controller failure. Existing controller failure detection and recovery mechanisms are performed in local controllers, which may degrade the performance of the local controllers. In controller failure recovery, existing mechanisms did not consider the time-varying load standard deviation metric, which may be used to reduce the flow setup time. To address these problems, we propose a Simulated Annealing-based Efficient Failover (SAEF) mechanism, run as an app in global controllers, to relieve the burden of local controllers for high availability hierarchical SDN controllers. The SAEF uses multiple global controllers to detect a local controller failure and compute a switch migration plan to redo switch-controller association for controller failure recovery. In controller failure detection, global controllers exchange their failure detection results of local controllers to jointly make a local controller failure decision to reduce the mistake rate. In controller failure recovery, the SAEF considers two metrics: switch-controller propagation delay and load standard deviation among local controllers with adaptive weights to adapt to time-varying local controllers' loads. In addition, in our design, a switch is connected to two local controllers so that asynchronous messages, such as packet-in and port-status messages, will not be lost during controller failover. Experiment results using EstiNet show that, the SAEF can achieve efficient failover with the best load balance result in term of load balance metric (LBM) of 1.035, while the best LBM of related works is 1.087. The SAEF also has the lowest flow setup time of 7.837 ms, while the best of related works is 10.418 ms. The lower flow setup time implies that the SDN data plane can receive the response message of a packet-in message faster.

In the software defined networks (SDN), the flow table of an OpenFlow switch is usually implemented by the ternary content addressable memory (TCAM). The TCAM has limited capacity which may cause the flow table overflow problem. To address the problem, related works perform a rule replacement scheme according to either the estimated next- packet arrival time of each flow or the hit count of each rule; however, it may remove a rule whose packets will soon arrive at a switch, especially when the network is unstable. This paper proposes a novel TCAM management scheme named in-switch rule caching and replacement (IRCR) to better deal with the flow table overflow problem. The IRCR replaces a rule according to the expected number of incoming matched flows (EIMF), which can be derived from the inter-arrival time distribution models of the corresponding flows. The uniqueness of the IRCR is that it is designed as an in-switch application to avoid link delays between controllers and switches. Using either captured real network traffic or uniform distribution traffic, the IRCR outperforms related works for both exactly matched rules and wildcard rules in terms of hit ratios. In addition, the IRCR has little overhead to the switch.

Load balancing among multiple controllers is a critical issue in the software-defined networking (SDN), since traffic dynamics prevent control-plane loads from being evenly distributed among controllers. Load imbalance may cause some controllers to be overloaded while the other controllers are still underutilized. Though there have been several proposed solutions, theydo not consider the convergence time of load balancing. We thus propose a fast-converging loadbalancing (FCLB) mechanism that seeks to achieve fast convergence for balancing loads (i.e., assigning switches) among the SDN controllers. Fast convergence can rapidly release controllersfrom being overloaded, thereby shortly recovering network performance and preventing some unanticipated results (e.g., controller crash). Searching for the optimal solution from a large set of switch-controller combinations can lead to a large delay, which can aggravate negative impacts from overloading. We thus leverage the genetic algorithm to lind a near-optimal solutionOur simulation results show that FCLB has at least 20.7% faster convergence time than the other mechanisms while achieving better load balancing performance.

With numerous emerging internet of things (IoT) devices, they generate big data. The big data transmitted to the cloud or fog will consume massive network bandwidth. This may result in the IoT network easily encountering network congestion. Moreover, there are IoT applications that need to transfer multimedia data with multiple quality of service (QoS) requirements. A state-of-the-art, MINA, intends to meet multiple QoS requirements of IoT applications; however, it is unable to guarantee QoS requirements of high-priority IoT applications and it is also unable to adapt to the current network status. To conquer the above problems, we propose an application-aware QoS routing algorithm (AQRA) for SDN-based IoT networking to guarantee multiple QoS requirements of high-priority IoT applications and to adapt to the current network status for better routing paths. Evaluation results have shown that, the AQRA has better fitness ratios of QoS requirements compared to MINA while multiple QoS requirements of high-priority IoT applications are guaranteed. The AQRA improves the average end-to-end flow performance by 10.75%, 11.88% and 10.82% compared to MINA in terms of delay, jitter and packet loss rate, respectively. The AQRA improves the standard deviation of end-to-end flow performance by 14.37%, 17.95% and 14.28% compared to MINA in terms of delay, jitter and packet loss rate, respectively. In addition, the runtime of the AQRA is 38.56% shorter than that of MINA.

The limited size of the flow table, usually implemented by ternary content addressable memory (TCAM), may result in the flow table overflow problem, which becomes severer in software defined networks (SDN). To conquer this problem, this paper proposes an in-switch dynamic flow aggregation (IDFA) mechanism, which can be dynamically triggered. In the IDFA, redundant flow entries are inserted to speed up flow aggregation convergence time. The uniqueness of the proposed IDFA is that it resides in an OpenFlow switch, instead of acting as an application in an SDN controller, which avoids link delays between the controller and switches. This paper also proposes two novel techniques, degradation and repermutation, to aggregate flows effectively while keeping semantic equivalence. Evaluation results show that, the average compression ratio of the IDFA in a fat-tree topology under a LAN (random IP) environment is 26.3% (43%) better than that of the Flow Table Reduction Scheme (FTRS), a representative related work. The average flow aggregation convergence time of the IDFA in the fat-tree topology is 84% shorter than that of the FTRS. In addition, the occurrence probability of flow table overflow in the fat-tree topology is 26.71 % lower than that of the FTRS.

Software-Defined Networking (SDN) benefits from the development flexibility of control-plane applications (SDN-Apps), which allows third parties to make contributions. Such flexibility may expose SDN networks to security threats, since SDN-Apps may be malicious or prone to implementation bugs. These buggy/malicious SDN-Apps may contaminate the data plane with abnormal network actions, which may not be prevented before they are committed to the data plane. This contamination may lead to network crash or poor network performance. We thus present ReSDN, a lightweight solution for data-plane state recovery, to recover an SDN data plane from a contaminated state. It requires neither switch modification nor the intervention of SDN-Apps, both of which current recovery solutions rely on. It leverages the concept of FP-tree (Frequent Pattern tree) to maintain the dependency of event transactions and network actions to achieve correct recovery. Our evaluations validate the viability of our ReSDN design, and show that it can recover more than twice as fast as the other type of recovery approach, rollback recovery.

WiGig enables wireless multi-gigabit communication over 60GHz band. However, its usage scenarios may be constrained by two major limitations: line-of-sight propagation and very short transmission range. We seek to boost the WiGig's usability by using WiFi to complement its limitations in tri-band (2.4/5/60GHz) wireless systems. Our goal is to let a tri-band client have multimedia services at the WiGig's very high speed without any hassle. When the WiGig link is down or performs bad, not only can the client temporarily handover to WiFi without service interruption, but its ongoing multimedia services can also adapt to the WiFi's slower link. Though the IEEE 802.11ad standard has proposed an FST (Fast Session Transfer) mechanism to support handover operations at the link layer, it does not satisfy our goal due to two reasons. First, it does not specify when to perform WiGig/WiFi handovers. Second, it is not application-aware to achieve the service adaptation. To this end, we design and implement an application-aware, seamless WiGig/WiFi handover solution above the network layer. It ensures timely handover trigger for the WiGig's abrupt link interruption, keeps service continuity during handovers, and adapts multimedia service qualities to different WiGig/WiFi links. Our demo confirms its viability. We show that a video streaming service at the client is not interrupted during WiGig/WiFi handovers, which are triggered by mobility or the WiGig's signal blockage, but smoothly switches between different resolutions according to different links.

The Software Defined Networking (SDN), an efficient network technology, allows researchers to program their networks to meet different application needs. In this paper, we focus on failure detection services in multiple SDN controllers. We review some classical failure detection services and discuss how these services work. These classical failure detection services have the high mistake rate problem. To deal with this problem, we propose a failure detection service with low mistake rates (FDLM) mechanism. We use a modified gossip protocol to distribute heartbeat messages and have multiple controllers to make failure decisions in order to achieve low mistake rates. Experiment results show that the proposed FDLM has better performance in terms of average mistake rate, 95.5% (79.8%) lower, compared to Akka under message loss for the case of four (three) controllers. The significance of achieving low mistake rates in the proposed FDLM is decreasing unnecessary SDN controller failover, which causes overheads of reelecting a leader controller, restarting a controller and synchronizing the restarted controller with the leader controller.

ABSTRACT Botnet has become one major Internet security issue in recent years. Although signature‐based solutions are accurate, it is not possible to detect bot variants in real‐time. In this paper, we propose behavior‐based botnet detection in parallel (BBDP). BBDP adopts a fuzzy pattern recognition approach to detect bots. It detects a bot based on anomaly behavior in domain name service (DNS) queries and transmission control protocol (TCP) requests. With the design objectives of being efficient and accurate, a bot is detected using the proposed five‐stage process, including: (i) traffic reduction, which shrinks an input trace by deleting unnecessary packets; (ii) feature extraction, which extracts features from a shrunk trace; (iii) data partitioning, which divides features into smaller pieces; (iv) DNS detection phase, which detects bots based on DNS features; and (v) TCP detection phase, which detects bots based on TCP features. The detection phases, which consume approximately 90% of the total detection time, can be dispatched to multiple servers in parallel and make detection in real‐time. The large scale experiments with the Windows Azure cloud service show that BBDP achieves a high true positive rate (95%+) and a low false positive rate ( ∼ 3%). Meanwhile, experiments also show that the performance of BBDP can scale up linearly with the number of servers used to detect bots. Copyright © 2013 John Wiley & Sons, Ltd.

Stable and efficient routing plays a key role for the success of VANETs. Road-based routing has been shown well-suited for urban VANETs, and multipath routing provides alternative routes once the current route fails. However, existing multipath routing protocols are node-based, which are not suitable for urban VANETs. In this paper, we propose a road-based QoS-aware multipath routing protocol for urban VANETs (RMRV). The proposed RMRV can find multiple paths and intelligently utilize them. We also propose a space-time planar graph approach to predict the connectivity of each road section (RS) in a path, and then derive the path's future lifetime and life periods. In this way, the source node may dynamically switch to use a path with the longest lifetime. The life periods of a path can further be utilized to estimate the packet delay for QoS routing. Simulation results show that comparing to RBVT-R, which is a single-path road-based routing protocol, the packet delivery ratio of the proposed RMRV (only one path used at a time) is 12.2% higher than that of RBVT-R, and the average end-to-end delay of RMRV is 11.5% lower than that of RBVT-R, on average. To the best of our knowledge, there is no existing road-based multipath routing protocol for VANETs.

A massively multiplayer online game (MMOG) has hundreds of thousands of players who play in the game concurrently. The players consume a great deal of CPU, memory and network bandwidth resources in MMOGs. We combine MMOGs with cloud computing environments. We use virtual machine servers (VMSs) in cloud computing environments instead of traditional physical game servers. By using a multi-server architecture, we divide a game world into several zones, and each zone consists of at least a VMS to execute game processes and exchange game information among players in the zone. In addition, we design an adaptive neural fuzzy inference system (ANFIS) and also an artificial neural network (ANN) to predict the load of each zone and decide a resource allocation policy to be performed by the VMS. Experimental results show that the mean square error of the ANFIS-based load prediction is lower than that of the ANN-based load prediction. Therefore, we incorporate the ANFIS prediction method along with the five resource allocation policies to the MMOG cloud. In terms of average access time, the proposed ANFIS-based DLP+SVMS resource allocation method is 16.7% better than the ANFIS-based DLP, where DLP is an existing deep-level partitioning (DLP) method. Furthermore, the proposed method has the smallest number of VMSs used among the three methods. The evaluation results show the feasibility of applying the proposed resource allocation method to MMOG clouds.

Infotainment service is getting popular in vehicular ad hoc networks (VANETs). Through inter-vehicle communication, vehicles can retrieve data from other vehicles, including multimedia data. In this paper, we propose an Overlay Multicast for VANETs (OMV). In OMV, interested vehicles (called group member nodes) join a multicast tree initiated by a vehicle providing multimedia data as the multicast source node, and the group member nodes are organized as an overlay structure. The OMV has a characteristic of dynamically adaptive to the road layout for urban VANETs. We present two new strategies, locally adapting to road intersections and globally probing for a better parent, to support the characteristic. Simulation results show that under a real setting of IEEE 802.11p, a vehicle mobility model, and a urban road layout, for group size under 20, the data delivery ratio can be 0.8 or more.

Existing data dissemination protocols adopted flooding to propagate interests and find forwarding paths in wireless sensor networks (WSNs), which cause large energy consumption. To relieve this problem, we propose an efficient cluster-based data dissemination (ECDD) scheme. In the proposed ECDD, besides piggyback control information into interests to perform on-demand passive clustering, we also use control information to set each node a hop count for assisting a node to select next forwarding node with the least hop count to the sink. In this way, a shortest path to forward sensed data back to the sink can be found. Simulation results show that the proposed ECDD is 61.30% better than DD, a classical approach, and 22.33% better than ELPC in terms of average dissipated energy. Furthermore, our approach is 57.45% and 23.49% better than DD and ELPC, respectively, in terms of average delay. The proposed ECDD is feasible for applications of long-term monitoring and real-time response, such as a community health care system and rescue operation in a disaster area.

P2P SIP (peer to peer session initiation protocol) systems have emerged as a new trend in multimedia realm due to their abilities to overcome the shortcomings of conventional SIP systems. Most of P2P SIP systems were implemented using Chord, a Distributed Hash Table (DHT) based routing algorithm which can provide scalability and reliability. Previous studies on P2P SIP systems did not address node heterogeneity, location information and mobility issues all together. For node heterogeneity, nodes with different capabilities (processing power, storage and bandwidth) should be treated suitably. For location information, the signaling latency is correlated with the distance between end users. This will influence call setup latency greatly. As to mobility, the node churn property will involve additional messages to maintain a stable DHT-based network and increases call setup latency. To conquer these problems, we propose a hierarchical social network-based P2P SIP system. The social network property can increase routing efficiency when calling friends. In addition, the proposed hybrid (structured/ unstructured) overlay is more resilient to cope with node churn. Simulation results show that our approach can improve 32% call setup latency with non-buddies and reduce 63% maintenance cost in comparison with the conventional Chord-based approach. In addition, we improve lookup efficiency from O(logN) to O(1) when making calls with buddies, where N is the number of nodes in a DHT-based network.

P2P (peer-to-peer) streaming systems are getting more and more popular in recent years. P2P streaming architectures can be classified into tree-based and mesh-based. The tree-based architecture has low start-up delay, but is less resilient to node failures compared to the mesh-based architecture, and it would result in a low delivery ratio and unstable quality of received multimedia. In this paper, we propose an efficient P2P multi-streaming scheme called HyStream based on application level multicast to resolve these problems. First, we split video streaming data and build multiple trees to transfer streaming data. Second, we incorporate a forward error correction (FEC) algorithm to recover lost data. Finally, we integrate a pull-based method with the tree-based architecture, which is a push-based method. When encountering data loss, we use a pull-based data retransmission method to retrieve lost data. Simulation results show that the proposed HyStream has 11.7% improvement in delivery ratio against SplitStream under various node failure rates. The delivery ratio of HyStream is 2.2% higher than that of CoolStreaming in a peer churn environment. The start-up delay of 90thpercentile nodes of HyStream is 35 seconds shorter than that of CoolStreaming. Note that our approach has small overhead of 6% redundant packets due to FEC, compared to SplitStream and CoolStreaming. In addition, HyStream has no more than 0.5% extra control overhead compared to SplitStream and CoolStreaming, even in a high peer churn environment.

In this paper, we designed and implemented a dependable SIP-based clustered architecture for VoIP and multimedia applications, and also proposed an efficient OpenAIS-based SIP load balancing strategy (OSLB) that can balance proxy serverspsila load and achieve fast failover by reducing the number of failed calls when one of the dispatchers or one of the SIP proxy servers crashes. Experimental results show that our OSLB is comparable to an existing work, SIP load balancer, in terms of load balance metric (1.05 vs. 1.04). However, our OSLB reduces the number of failed calls by 86% when a proxy server failed compared to the SIP load balancer. This work, which is part of an EPON project, has been realized in an industry standard ATCA-based platform to provide high availability carrier-grade services, and is currently under a field trial in an ISP.

In this paper, we propose a deferred-workload-based inter-task DVS (dynamic voltage scaling) algorithm (dwDVS), which has two features, for portable multimedia devices. The first is that we reserve a time interval for each task to execute and its workload can be completed in this time interval even in the worst-case condition, which means that the actual workload (execution time) of each task is equal to its worst-case execution time. In this way, we can estimate the slack time from lower priority tasks more aggressively. The second is that we defer these reserved time intervals, which means that a reserved time interval will be shifted to the deadline of its corresponding task as close as possible. Thus, the operating frequency can be reduced even without slack time. Simulation results show that the proposed dwDVS reduces the energy consumption by 40-70%, 10-20%, and 3-10% compared with the static voltage scaling (Static), laEDF, and DRA algorithms, respectively, and approaches theoretical low bound (Bound) by a margin of at most 12%.

The IEEE 802.16e provides QoS for real-time traffic; however, the packet transmission delay due to the handover process is still a big concern. Therefore, a fast handover approach to minimize the blocking time of real-time traffic is necessary for providing QoS. In this paper, we present a novel network architecture for IEEE 802.16e, which is still compatible to the IEEE 802.16e standard. Based on this architecture, a network assisted fast handover scheme (NFHO) is proposed to shorten the handover time. Performance evaluation has shown that our proposed NFHO scheme reduces the service disruption time by 98.2% and 96.8% compared to association levels 1 and 2 / Choi et al. of the IEEE 802.16e, respectively, for scanning just one base station (BS). Our improvements will be even better if scanning more BSs. In addition, the proposed NFHO scheme reduces the service disruption time by 78.4% with five neighbouring BSs scanning compared to Lee et al.

The SIP proxy server, which is an important building block of a SIP network, can be in a form of a cluster to prevent service unavailability caused by software or hardware failures. The design of a SIP proxy server cluster with a single dispatcher in a SIP network faces the single-point-offailure problem. The use of dual SIP dispatcher architecture was proposed and VRRP (Virtual Router Redundancy Protocol) was used as an IP failover mechanism. In this paper, we have designed and implemented a dependable SIP network that includes n + k SIP dispatchers (n active dispatchers + k backup dispatchers) to control and monitor a cluster ofm SIP proxy servers for VoIP and video conferencing applications. A fast failure detection and failover (FFF) scheme has also been proposed. FFF uses OpenAIS as a high availability middleware to perform health check and failover of dispatchers and proxy servers. Experimental results have shown that the FFF scheme reduces the dispatcher failover time by 80 % compared to the VRRP mechanism and also shorten the proxy failover time by 85 % compared to the mechanism provided by OpenSER itself.

In the paper, we propose a novel scheduling mechanism without modifying the existing IEEE 802.11 MAC, called wireless radio-matching protocol (RMP). It takes account of interferences in wireless mesh networks to achieve maximum spatial reuse by using pre-specified radio transmissions. In contrast with existing random access methods, the RMP adopts a decentralized controlled access to avoid nodes from unintentional packet collisions. The RMP adopts a chain topology of bidirectional transmissions, where nodes are spaced so that radios of non-neighboring nodes do not interfere with each other. Simulation results indicate that the throughput of RMP is about 30% better than that of Ripple (R.-G. Cheng et al., 2006) and almost 200% better than that of the IEEE 802.11 DCF. Although RMP achieves higher throughput than Ripple, it still maintains the same delay time and transmission quality, as verified by our simulation results. The RMP achieved a stable throughput and a low end-to-end transmission delay in both CBR and FTP traffic compared to the IEEE 802.11 DCF. In addition, the RMP is simple, easy to implement, and it eliminates the back-off inefficiencies and the collision problem in IEEE 802.11 wireless environments.

There are few localization schemes targeted at mobile wireless sensor networks. This paper proposed an enhanced color-theory-based dynamic localization (E-CDL) which is based on the CDL algorithm (Shee, 2005). However, the location accuracy of this algorithm depends on the accuracy of the average hop distance derivation. Therefore, the authors present two novel schemes to estimate the average hop distance. The authors analyzed the behavior of sensor nodes communication, and computed the expected value of the average hop distance, which is 7r/9 where r is the radio range. In addition, since CDL is based on the DV-hop scheme, the derived shortest path length is usually larger than the corresponding Euclidean distance. With this observation, the derived shortest path length can be adjusted by the ratio of the Euclidean distance and the shortest path distance to further enhance the location accuracy. Finally, in mobile wireless sensor networks, sensor nodes may become isolated. By employing mobile anchor nodes, the isolation problem can be relieved and hence the location accuracy can be improved. Simulation results have shown that the location accuracy of E-CDL is 50%-55% better than that of CDL, and 75%-80% better than that of MCL (Monte Carlo localization) (Lingxuan and David, 2004), In addition, the authors have implemented and verified our algorithm on the MICAz Mote developer's kit.

Since the legacy IEEE 802.11 standard offers inadequate QoS support, IEEE 802.11e was proposed to provide QoS support for multimedia applications. However, for the enhanced distributed channel access (EDCA) of IEEE 802.11e, when a channel is occupied with high priority traffic, low priority traffic may suffer starvation due to its little chance of contending for the channel. The starvation of low priority traffic may result in failure of these digital home applications, which is unacceptable. DDRR was proposed to achieve this goal; however, it cannot be adapted to traffic condition dynamically. In this paper, we propose a QoS scheme, called starvation prevention for low-priority traffic (SPLPT), for digital home applications in IEEE 802.11e WLANs. SPLPT prevents starvation of low priority traffic by providing adequate contention-free channel access with its compensation procedure for starving traffic (CPST) when starvation is about to occur; and it has the same behavior as EDCA when the CPST is not activated. SPLPT integrates both EDCA and HCCA (HCF controlled channel access) of the IEEE 802.11e to provide high throughput performance as well as starvation prevention, and it is fully compatible to IEEE 802.11e. Simulation results have shown that when the WLAN is heavily loaded with high priority traffic, SPLPT shortens the IMAC delay of low priority traffic by 3.9 and 5.1 times, respectively, compared to EDCA and DDRR. In addition, the throughput of low priority traffic is raised up from 0% to 5% of the maximum throughput to avoid starvation.

We propose a Bluetooth channel state dependent data segmentation and reassembly (CSD-SAR) scheme and a queue state dependent priority (QSD-PR) scheduling policy. The CSD-SAR maintains a receiving frequency table to predict channel conditions and selects the best packet type and packet size to transmit data. In addition, the QSD-PR also uses the receiving frequency table to avoid bad frequencies and gives a selected master-slave pair, which has more queued data to send between each other and has a higher priority to eliminate the wastage of slots. The conventional scheduling policy, round robin (RR), yields poor performance with the time division duplex (TDD) based MAC protocol and results in slot wastage and may not ensure fairness. Simulation results show that our proposed scheme achieves better link utilization and higher throughput with bounded delay compared to the RR scheme in error-free and error-prone environments. Our scheme can also eliminate interference to other wireless networks that share the same spectrum, such as WLANs, by avoiding selecting channels occupied by other networks.

A novel Backus-Naur-form- (BNF-) based method to automatically generate test programs from simple to complex ones for advanced microprocessors is presented in this paper. We use X86 architecture to illustrate our design method. Our method is equally applicable to other processor architectures by redefining BNF production rules. Design issues for an automatic program generator (APG) are first outlined. We have resolved the design issues and implemented the APG by a top-down recursive descent parsing method which was originated from compiler design. Our APG can produce not only random test programs but also a sequence of instructions for a specific module to be tested by specifying a user menu-driven file. In addition, test programs generated by our APG have the features of no infinite loop, not entering illegal states, controllable data dependency, flexible program size, and data cache testable. Our method has been shown to be efficient and feasible for the development of an APG compared with other approaches. We have also developed a coverage tool to integrate with the APG. Experimental evaluation of the generated test programs indicates that our APG, with the guidance of the coverage tool, only needs to generate a small number of test programs to sustain high coverage.

In this paper, we propose a load balancing strategy that has the following features: (1) estimating the potential load of real gateways with low computation and no communication overhead, (2) asynchronous alarm sent when the utilization of a real gateway exceeds a critical threshold, and (3) WAP-awareness. We also propose a scalable WAP gateway (SWG) that consists of a WAP dispatcher and a cluster of real gateways. The WAP dispatcher is a front-end distributor with our load balancing strategy. To prevent the WAP dispatcher from becoming a bottleneck, the WAP dispatcher distributes mobile clients' requests in kernel space and does not process outgoing gateway-to-client responses. Experimental results show that our SWG has better load balancing performance, throughput, and delay compared to the LVS and the Kannel gateway. Although WAP services are not so popular as expected, our load balancing strategy, can be easily adapted to other distributed services.

This work designs and analyzes a cost-effective growable multicast asynchronous transfer mode (ATM) switch that has a new grouping network structure. The proposed switch can easily be enlarged by using more stages, since both cell routing and contention resolution are designed to distribute over the switch elements. Experimental results indicate that, by allowing valid cells to enter grouping networks from two directions (the west and north sides), the modular ATM switch proposed herein not only meets the ATM performance requirements for both unicasting and multicasting but also uses fewer switch elements and has a shorter cell delay than the ATM switch.

We propose a fuzzy-based approach which provides a soft threshold to determine the module size for CMOS circuit partitioning in built-in current testing (BICT). Experimental results show that our design approach indeed provides a feasible way to exploit the design space of BICT partitioning in comparison with other approaches with a fixed threshold, and a better module size can thus be determined to reflect a change of circuit properties.

Partitioning a digital circuit into modules before implementing it on a single chip is key to balancing between the test cost and test correctness of built-in current testing (BICT). Most partitioning methods use statistical analysis to find the threshold value and then to determine the size of a module. These methods are rigid and inflexible, since IDDQ testing requires the measurement of an analog quantity rather than a digital signal. In this paper, we propose a fuzzy-based approach which provides a soft threshold to determine the module size for BICT partitioning. Evaluation results show that our design approach indeed provides a feasible way to exploit the design space of BICT partitioning.

In this paper, we design and analyze a growable multicast ATM switch. It can grow to a large size since both cell routing and contention resolution are designed to distribute over the switch elements, and the switch structure is modular. The output ports are partitioned into groups to permit sharing of routing paths. The concept of group routing helps reduce an order of magnitude of switch elements. A two-stage switch architecture is described to illustrate our design principle. The switch can be easily expanded to a larger size by using more stages. The performance analysis of the switch in terms of cell loss rate, cell delay, mean queue length, mean waiting time, and throughput is conducted using the M/Geom/1 model. Experimental results show that the proposed ATM switch not only meets the ATM performance requirements either for unicasting or multicasting but also uses fewer switch elements and has less delay than other comparable switches.

In this paper, we present a novel and efficient approach to test MCM at the module as well as chip levels. Our design incorporates the concept of the multifrequency test method and the smart substrate to provide two levels at speed test. The IEEE 1149.1 boundary scan standard is used to offer the necessity of controllability and observability. Part of the boundary scan cells used in the chip level are modified to form the module level scan chain. Using the chip level boundary scan cells to provide both chip and module level testings, it not only decreases area overhead but also reduces extra delay introduced by the addition of test circuits. The contribution of this paper is to provide an MCM design for testability strategy which has the capability to detect performance defects as well as static faults with small delay and low overhead.

The authors present an integrated computer-aided design environment, the VAR (VHDL-based array reconfiguration) system, for the tasks of design, reconfiguration, simulation, and evaluation in an architecture modeled by VHDL. An easily diagnosable and reconfigurable two-dimensional defect-tolerant processing element (PE) switch lattice array is used as an example to illustrate the methodology of VAR. VAR allows the designers study and evaluate fault diagnosis and reconfiguration algorithms by inserting faults, which are generated based on manufacturing yield data, into the array and then locating the fault PEs as well as simulating the reconfiguration process. Thus, VAR can assist the designers in evaluating the different combinations of fault patterns, fault diagnosis algorithms, and reconfigurable architectures through a complete set of figures of merit which aim at architectural improvements. Extensive simulation and evaluation have been performed to demonstrate and support the effectiveness of VAR.>

A systematic and efficient fault diagnosis methodology in reconfigurable VLSI array architectures is presented. This methodology utilizes the output data path independence of subsets of processing elements (PEs) based on the topology of the arrays. The 'divide the conquer' technique is applied to reduce testing complexity and enhances the controllability and observability of arrays. An array under test is divided into several nonoverlapping parallel partitions. Those PEs in the same partition can be diagnosed simultaneously. The problem to find parallel partitions is shown equivalent to a generalized Eight Queens problem. Three types of easily testable PEs are designed to illustrate this approach. The main contribution of this paper is a novel PE fault diagnosis approach which speeds up the testing by at least O( mod V mod /sup 1/2/) for the arrays considered, where mod V mod is the number of PEs. This approach requires little or no hardware overhead depending on the types of architectures and can diagnose multiple PE faults.>