Internet of Things (IoT) sensors monitor temperature-sensitive goods throughout the supply chain. Nowadays, blockchain is being widely used for traceability, transparency, and immutable storage of this data. However, this approach lacks a mechanism to assess the trustworthiness of the data, and as a result, the reliability of the system is constrained by the quality of the data being added. IoT sensor data can be compromised for various reasons, including sensor malfunctions, deliberate tampering, or human error. This demonstration presents a solution that integrates machine learning techniques with blockchain to enhance data trust in cold chain logistics.

The convergence of blockchain and Internet of Things (IoT) has become increasingly prevalent recently, as it addresses challenges such as single point of failure and security concerns associated with IoT. Blockchain offers immutable data storage, availability, and transparency, but a significant drawback lies in its inability to verify the truthfulness of the data stored on it. State-of-the-art systems attempting to mitigate this concern often rely on conventional reputation-based approaches, which predominantly evaluate historical data from sensors and neglect the critical assessment of data in real-time. Furthermore, there is limited research on incorporating machine learning (ML) methods to enhance data trustworthiness in blockchain systems. This paper proposes a novel ML-based trust assessment approach that takes into account both historical reputation and real-time data trust-worthiness. Our approach integrates multiple ML models within a blockchain framework using edge servers and validators, effectively functioning as a distributed ensemble to enhance classification accuracy, and contributing to more accurate reputation score calculations. Our results demonstrate significant accuracy gains in distinguishing trustworthy and untrustworthy IoT sensor data in blockchain networks.

Recently, there has been a surge of interest surrounding the integration of blockchain with the Internet of Things (IoT), aiming to address IoT’s inherent issues like single points of failure and concerns related to data integrity. However, although blockchain provides decentralization and transparency, it does not guarantee the accuracy and reliability of IoT-generated data. Therefore, additional measures are needed to assess and verify the reliability of IoT data stored on blockchains. In this demonstration, we present a novel approach that employs support vector machine (SVM) models in edge servers and multiple machine learning (ML) models executed by validators for data trust evaluations in blockchain-enabled IoT systems. Our approach introduces a composite trust metric that combines past device reputation on the blockchain with real-time data assessment enabled by SVM models. This composite measure provides a dynamic method for determining the trustworthiness of data at the point of submission. The multiple different ML models used by validators work as a distributed ensemble, leading to improved classification accuracy. This novel approach helps to calculate reputation scores more accurately, increasing the system’s reliability. We illustrate the feasibility of our approach through a description of our prototype implementation.

Blockchain offers cryptographically secure storage for recording transactions. However, one issue with blockchains is the problem of bad data and data reliability, where bad data refers to inaccurate, incomplete, or irrelevant data. This paper investigates how machine learning (ML) can be used to identify inaccurate sensor data added to a blockchain in Internet of Vehicles (IoV) applications. A solution for reducing the inclusion of incorrect data using a reputation-based method is proposed. We suggest that if an accurate ML model can be built for a task that can be completed using the input sensor data, it is possible to use the same model to assess the accuracy of new input data samples for which the actual task outcome is known. A road surface-type classification task is performed using Convolutional Neural Network models on the Passive Vehicular Sensors Datasets, and a pre-trained model is used in a novel solution approach involving edge servers and validators on a blockchain network. Our research shows that ML can be used to identify bad data on the blockchain and to reduce the addition of unreliable data to the blockchain in an IoV context. The proposed solution is generalizable and can be applied to any scenario where an accurate ML model can be devised for a task that can be accomplished using some blockchain input data.

Processing large scientific applications generates a huge amount of data, which makes running experiments in the cloud computing environment very expensive and energy-consuming. To find an optimal solution to the workflow scheduling problem, several approaches have been presented for scheduling workflow on cloud resources. However, more efficient approaches are needed to improve cloud service delivery. In this paper, an energy-efficient virtual machine mapping algorithm (EViMA) is proposed to improve resource management in the cloud computing environment to achieve effective scheduling that reduces cloud data center energy consumption, execution makespan, and execution cost. This ensures that the requirements of cloud users are met, and improves the quality of services offered by cloud providers. Our proposed mechanism considers the heterogeneity of scheduling from both cloud users’ and workflow applications’ perspectives. Through simulation experiments on real workflow datasets, the proposed EViMA can provide better solutions for both cloud users and cloud providers by reducing energy consumption, execution makespan, and execution cost better than the state-of-the-art.

Providing support for energy efficiency and Quality of Service (QoS) is among the major challenges when designing solutions for video delivery over Wireless Multimedia Sensor Networks (WMSN). As video applications have high bitrate delivery requirements, an effective way is to enable the sensor nodes to transmit data over multiple paths in parallel, for instance by employing Multi-path TCP (MPTCP). However, in a dense network like WMSN, high traffic volume transmission may cause congestion, affecting all paths. In such a case, congestion control algorithms play a key role in order to support high QoS levels, including by employing retransmissions of lost data. However, data retransmissions result in energy consumption increases, which is an aspect of concern for WMSN services. In this paper, we propose eqCCMP, an energy-efficient congestion control scheme for MPTCP. The general idea of eqCCMP is to use low energy consumption paths to deliver data, while making sure good QoS levels are maintained. A fluid model is employed to formulate the operation of eqCCMP. The performance of eqCCMP is evaluated in comparison with other schemes including the vanilla MPTCP and ecMTCP. By considering an extra factor in the congestion avoidance phase for congestion window adjustment, the proposed eqCCMP outperforms the other solutions in terms of throughput and energy efficiency in a simulation environment.

Vehicular communication systems have significant benefits. Their adoption and use in motor vehicles can help prevent road traffic accidents, increase route efficiency and fuel economy, and positively impact the user experience. As autonomous vehicles and inter-vehicular communication systems are becoming increasingly commonplace, the need for robust and secure wireless communication between vehicles is essential. The black hole attack is an attack vector that can significantly reduce the availability of Vehicular Ad Hoc Networks (VANETs) and prevent communication between vehicles entirely. We propose a solution to help secure these networks against this vulnerability by detecting the attack and removing the malicious node from the network. We validated our proposal using a simulation model in NS-3; results show that our system can detect, stop, and prevent black hole attacks in VANETs.

Microscopic traffic simulation is the most accurate tool for predictive analytics in urban environments. However, the amount of workload (i.e., cars simulated simultaneously) can be challenging for classical systems, particularly for scenarios requiring faster than real-time processing (e.g., for emergency units having to make quick decisions on traffic management). This challenge can be tackled with distributed simulations by sharing the load between simulation engines running on different computing nodes, hence balancing the processing power required. This paper studies the performance of dSUMO, i.e., a distributed microscopic traffic simulator. dSUMO is fully decentralized and can dynamically balance the workload between its computing nodes, hence showing important improvements against classical, centralized and not dynamic, solutions.

This work proposes a novel Delay-aware Packet Prioritisation Mechanism (DPPM) to uniformly distribute the Quality of Service (QoS) level across all Voice Over IP (VoIP) calls in a Wireless Mesh Network (WMN). The method prioritises VoIP packets based on the amount of queueing delay that has been accumulated across multiple hops within the WMN. The accumulated queueing delay is piggybacked over every VoIP packet and is used at the enqueueing phase to place more delayed packets towards the head of the queue. This assures higher priority for more delayed VoIP packets over less delayed VoIP packets. The influence of the queueing delay on voice call quality is further reduced by utilising the proposed DPPM in conjunction with WiFi frame aggregation. This conjunction increases the network's VoIP call capacity, and this is validated through NS-3 simulations.

Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer linear programming (MILP) approaches, especially given the size of data centres. The multi-objective version of the Machine Reassignment Problem is even more challenging and it seems unlikely for CP or MILP to obtain good results in this context. As a result, the first approaches to address this problem have been based on other optimisation methods, including metaheuristics. In this paper we study under which conditions a mixed integer optimisation solver, such as IBM ILOG CPLEX, can be used for the Multi-objective Machine Reassignment Problem. We show that it is useful only for small or medium scale data centres and with some relaxations, such as an optimality tolerance gap and a limited number of directions explored in the search space. Building on this study, we also investigate a hybrid approach, feeding a metaheuristic with the results of CPLEX, and we show that the gains are important in terms of quality of the set of Pareto solutions (+126.9% against the metaheuristic alone and +17.8% against CPLEX alone) and number of solutions (8.9 times more than CPLEX), while the processing time increases only by 6% in comparison to CPLEX for execution times larger than 100 seconds.

In this paper, we present an experimental evaluation of the recently standardized Opus codec used in a VoIP context. Opus operates in both narrow and wideband modes, similar to Adaptive Multi-Rate (AMR). Through the use of the Wideband Perceptual Evaluation of Speech Quality (WB-PESQ) metric, we have conducted an extensive set of experiments using multiple audio samples encoded at different bit-rates, to investigate the impact of packet loss on resulting speech quality. Using these results, fitting functions for each bit-rate were computed to provide a straightforward manner of evaluating speech quality when given a specified packet loss rate. Using ns-2, a simulation analysis was conducted to evaluate the effect of background traffic on transmitted Opus streams. We observed that, when using different levels of background traffic, the observed packet loss rates varied heavily depending on the stream bit-rate. By correlating this information with the fitting functions derived previously, we were able to define switching thresholds. These are points where the speech quality of a lower bit-rate stream is greater than that of a higher bit-rate stream for the same levels of link bandwidth saturation.

Synchronisation mechanisms are essential in distributed simulation. Some systems rely on central units to control the simulation but central units are known to be bottlenecks. If we want to avoid using a central unit to optimise the simulation speed, we lose the capacity to act on the simulation at a global scale. Being able to act on the entire simulation is an important feature which allows to dynamically load-balance a distributed simulation. While some local partitioning algorithms exist, their lack of global view reduces their efficiency. Running a global partitioning algorithm without central unit requires a synchronisation of all logical processes (LPs) at the same step. The first algorithm requires the knowledge of some topological properties of the network while the second algorithm works without any requirement. The algorithms are detailed and compared against each other. An evaluation shows the benefits of using a global dynamic load-balancing for distributed simulations.

The purpose of this paper is to highlight the utility of publicly released urban data-sets and, more specifically, to detail how our analysis was undertaken and to demonstrate the interesting insights regarding vehicular traffic that can be gained from this analysis. This paper uses a data-set provided by Dublin City Council from their Travel-time Reporting and Integrated Performance System (TRIPS). Data from all 45 routes covered by TRIPS was continually collected over the course of a number of months for analysis. From these routes, 4 were selected for detailed analysis. It can be observed that while the routes themselves exhibit some levels of self-similarity, when compared to each other, in some cases their behaviors are distinct. These behaviors are assessed from a number of different aspects to gain insights. Finally, to highlight how data related to vehicular traffic can be used to aid the public, an outline of an application which provides recommendations to commuters is provided. The purpose of this application is to utilise the previously discussed data and analysis to help minimise an individual's commuting time.

Using modelling to predict the performance characteristics of software applications typically uses Queueing Network Models representing the various system hardware resources. Leaving out the software resources, such as the limited number of threads, in such models leads to a reduced prediction accuracy. Accounting for Software Contention is a challenging task as existing techniques to model software components are complex and require deep knowledge of the software architecture. Furthermore, they also require complex measurement processes to obtain the model's service demands. In addition, solving the resultant model usually require simulation solvers which are often time consuming.

omputing servers generally have a narrow dynamic power range. For instance, even completely idle servers consume between 50% and 70% of their peak power. Since the usage rate of the server has the main influence on its power consumption, energy-efficiency is achieved whenever the utilization of the servers that are powered on reaches its peak. For this purpose, enterprises generally adopt the following technique: consolidate as many workloads as possible via virtualization in a minimum amount of servers (i.e. maximize utilization) and power down the ones that remain idle (i.e. reduce power consumption). However, such approach can severely impact servers' performance and reliability. In this paper, we propose a methodology to determine the ideal values for power consumption and utilization for a server without performance degradation. We accomplish this through a series of experiments using two typical types of workloads commonly found in enterprises: TPC-H and SPECpower ssj2008 benchmarks. We use the first to measure the amount of queries responded successfully per hour for different numbers of users (i.e. [email protected]) in the VM. Moreover, we use the latter to measure the power consumption and number of operations successfully handled by a VM at different target loads. We conducted experiments varying the utilization level and number of users for different VMs and the results show that it is possible to reach the maximum value of power consumption for a server, without experiencing performance degradations when running indi- vidual, or mixing workloads.

In a heterogeneous cloud environment, the manual grading of computing assets is the first step in the process of configuring IT infrastructures to ensure optimal utilization of resources. Grading the efficiency of computing assets is however, a difficult, subjective and time consuming manual task. Thus, an automatic efficiency grading algorithm is highly desirable. In this paper, we compare the effectiveness of the different criteria used in the manual grading task for automatically determining the efficiency grading of a computing asset. We report results on a dataset of 1,200 assets from two different data centers in IBM Toronto. Our preliminary results show that electrical costs (associated with power and cooling) appear to be even more informative than hardware and age based criteria as a means of determining the efficiency grade of an asset. Our analysis also indicates that the effectiveness of the various efficiency criteria is dependent on the asset demographic of the data centre under consideration.

The primary contribution of this paper is the design of a novel architecture and mechanisms to enable voice services to be deployed over femtocells backhauled using a wireless mesh network. The architecture combines three mechanisms designed to improve Voice Over IP (VoIP) call quality and capacity in a deployment comprised of meshed femtocells backhauled over a WiFi-based Wireless Mesh Network (WMN), or femto-over-mesh. The three mechanisms are: (i) a Call Admission Control (CAC) mechanism employed to protect the network against congestion; (ii) the frame aggregation feature of the 802.11e protocol which allows multiple smaller frames to be aggregated into a single larger frame; and (iii) a novel delay-piggy-backing mechanism with two key benefits: prioritizing delayed packets over less delayed packets, and enabling the measurement of voice call quality at intermediate network nodes rather than just at the path end-points. The results show that the combination of the three mechanisms improves the system capacity for high quality voice calls while preventing the network from accepting calls which would result in call quality degradation across all calls, and while maximizing the call capacity available with a given set of network resources.

Current trends show a growing number of femtocell deployments, this in turn will lead to increased volumes of voice traffic being transmitted through fixed broadband access networks such as Digital Subscriber Line. In this paper the issue of maintaining call quality through the resource constraint expedited forwarding queue of DSLAMs is investigated. A quality based Call Admission Control and resource allocation mechanism is provided to avoid resource overloading and call quality degradation. The ITU-T's E-Model is used for call quality monitoring and a message exchange interface between the mobile and fixed networks which allows dynamic adjustment to network resources is described and simulated. The results show that high voice call quality can be maintained.

Traffic simulation can be very computationally intensive, especially for microscopic simulations of large urban areas (tens of thousands of road segments, hundreds of thousands of agents) and when real-time or better than real-time simulation is required. For instance, running a couple of what-if scenarios for road management authorities/police during a road incident: time is a hard constraint and the size of the simulation is relatively high. Hence the need for distributed simulations and for optimal space partitioning algorithms, ensuring an even distribution of the load and minimal communication between computing nodes. In this paper we describe a distributed version of SUMO, a simulator of urban mobility, and SParTSim, a space partitioning algorithm guided by road network for distributed simulations. It outperforms classical uniform space partitioning in terms of road segment cuts and load-balancing.

There is already a vast literature on the efficiency of the 802.11a MAC using Markov Chain models. This current literature states that the output of these mathematical models are aggregated throughput values related to the number of radios sharing the same physical medium. The study presented in this paper shows an inaccuracy in the proposed Markov Chain models; when increasing the number of radios for saturated 802.11a MAC links using the Distributed Coordination Function the models no longer return true aggregated throughput values. The evaluation process of the presented work is based on aggregated throughput, delay and delay variation results obtained from conducted simulations and experiments. It will be further shown that more than three radios which are saturating the 802.11a MAC and sharing the same medium will lead to an unacceptable network performance. The evaluation of the results is based on ITU-T recommendations for IP networks under predefined network topology assumptions.

In this paper the accuracy and distribution of measured 802.11 Receive Signal Strength values will be analysed using three different Atheros based cards. The analysis is performed using empirical methods, e.g., sample mean and Empirical Cumulative Distribution Functions, in order to demonstrate the dependency of the accuracy of Receive Signal Strength values on the used chipset and on the number of captured frames to derive the sample mean with a certain probability. A comprehensive section on the experimental environment ensures a possible repeatability of the measurements which underlines the complexity of the performed analysis at the same time.

The increasing number of users demanding voice and data communication through cellular networks has driven the need for higher network throughput rates and lower latency. LTE femtocells address this pressing problem by offloading cellular service providers networks and increase both coverage and capacity for their users. Assuming a wired DSL backhaul for these femtocells, this paper shows simulations exploring a case where the DSLAM represents the main bottleneck when the cellular network operator and the DSL provider do not collaborate. This paper introduces the concept of Intermediary Mean Opinion Score which may be employed at femtocell gateways to isolate network problems and feed into customer experience management. We also propose and investigate a technique of mapping the human audio recency into the MOS calculation. Results are presented to illustrate the information that can be extracted from a lightweight monitor in the network.

The existence of hidden and exposed nodes can have a significant negative impact on the performance of IEEE802.11 networks. Such nodes can increase the probability of collisions and limit the spatial reuse on the channel. The value of the Physical Carrier Sensing Threshold (PCST) is instrumental in the presence of such nodes in a system. This paper presents a new adaptive physical carrier sensing management algorithm for wireless networks. Our KAPCS2 management system maximizes the aggregate system throughput by identifying and addressing problem nodes. It incorporates 802.11k Radio Resource Measurements (RRM) on each node to enable on-line tuning of the PCST.

The availability of reasonably priced, increasingly powerful, mobile devices is driving the growth of new video content services. One likely solution for video content delivery is based on the Peer-to-Peer (P2P) architecture. Network congestion can have a significantly negative impact on the performance of P2P distribution. This paper focuses on enabling effective P2P content distribution over radio access networks. We developed a IEEE802.11k assisted mechanism to perform load balancing of peer associations across available networks. Load balancing can reduce congestion and increase throughput. Simulation results show significant throughput increase following a handover.

Composing large enterprise applications from reusable software components has become a major software development technique. Components are considered as black boxes and are composed together by their provided and required services. In comparison to other software development approaches, this allows for rapid development, clean and explicit architectures, and easy component reuse. Currently, there are several systems that support development and composition of components: service component architecture and Fractal are two well-known ones. At first sight, both have the same goals and provide very similar means to developers. In this paper, we briefly present both systems and then we focus on an in-depth comparison and evaluation of them.

This paper examines two specific aspects of resource management in Wireless Local Area Networks (WLANs)-Call Admission Control (CAC) and handling of Link Adaptation (LA) events. A self-consistent system to manage these for Voice over Internet Protocol (VoIP) over an IEEE 802.11 WLAN is presented. The proposed CAC scheme is based on the Endpoint Admission Control (EAC) paradigm, where the endpoints probe the network to determine if the call can be supported with acceptable Quality of Service (QoS). The proposed scheme was evaluated on an experimental testbed and test results show that correct admission decisions were made under various network configurations. The scheme also determines if LA has resulted in the system becoming congested and, if so, the voice codec of the handset which has undergone LA is adapted so as to restore the system to its earlier state, thereby alleviating the congestion. The proposed scheme was evaluated on the experimental testbed and test results show that the codec adaptation scheme was very effective at overcoming the effects of LA for VoIP over WLAN.

In this paper, two formulations for planning base station (BS) and Relay Station (RS) locations are proposed: a rather complex 0-1 integer programming model which can be used to determine which set of locations should be selected from a given set of BS and RS locations and a simpler decomposition approach which focuses first on the BS location problem followed by the RS location determination. The two approaches are compared and the results show that the simpler decomposition approach can find solutions using significantly less resources which are very minimally lower in quality than that found by the more complex formulation. Hence, the decomposition approach can be used to solve larger 802.16j network planning problems.

In this article, we design, implement, and analyze a scalable Live VOD services distribution architecture that offers higher video services reliability for a fraction of the current cost. Our solution (RS-VOD) is based on a P2P retransmission system where end-users retransmit lost packets to each other, thereby reducing the retransmission burden on the video servers. Video receivers tuned to the same video stream are organized in an overlay network of retransmission peers that exchange useful statistics and performance metrics describing the network conditions affecting their respective received video streams. Signalling data exchanged among retransmission peers include: loss rate measurements, packet loss pattern, round-trip-time (RTT) measurements, etc. Based on this real-time information exchange, each receiver assesses the suitability of each retransmission peer before allocating a retransmission load for each of them. We show that the service provider can use several strategies to control the process of selecting retransmission peers and outperform in different network conditions. Several decision models have been implemented and analyzed in this article. We also highlight the major findings and tradeoffs in a P2P retransmission system.

The emerging Media Independent Handover (MIH) standard proposes to support session continuity during handover between heterogeneous networks. One of the critical features provided by MIH is an Event Service which includes predictive network degradation events, such as Link_Going_Down (LGD), which are triggered based on link layer metrics. Our results highlight the reactivness of media stream quality to network degradation. The point of degradation however, is specific to the characteristics of the class of media streaming service. Many existing event algorithms utilize static performance thresholds which are unresponsive to the requirements of individual application service classes. In this paper we propose a Service Oriented Link Triggering Algorithm (SOLTA) which triggers the LGD and Link_Down (LD) events based on link layer metrics but subject to the performance characteristics of the supported class of service. SOLTA illustrates that for 802.11, it is necessary to have aggressive service class specific, link event triggering. SOLTA also illustrates how a soft path handover approach such as Stream Control Transmission Protocols Concurrent Multi-path Transfer (SCTP-CMT) variant is necessary to support seamless session migration.

Multi-source streaming is essential for the design of a large-scale P2P streaming architecture. In this paper, we focus on improving the dependability of multi-source video streaming as an alternative to the more prevalent point-to-point streaming. We have designed and implemented a dynamic FEC (D-FEC) protocol for multi-source video streaming. Our D-FEC protocol has the ability to dynamically switch between 4 different FEC techniques to adapt to varying network conditions. A comprehensive performance evaluation was performed with a full-scale system prototype that gives insights into the behavior of the different adaptive FEC schemes, and shows the feasibility of the concept of switching FEC schemes during a streaming session. Guidelines are given in order to best design a FEC protocol switching strategy taking into account the experienced loss rate, the loss burstiness, and the original video stream rate.

Wireless mesh networking is a promising, cost effective and efficient technology for realizing backhaul networks supporting high quality services. In such networks, multicast data are transmitted blindly without any mechanism protecting data from loss, ensuring data reception, and optimizing channel allocation. The multicast services may undergo, then, very high data loss ratio which is exacerbated with the number of hops. In this paper, we propose a Reliable Multicast Distribution System (RMDS) to optimize multicast packets transmission in bridged networks. Relying on a modification of the IGMP snooping protocol, RMDS enables reliable services provisioning support in common wireless mesh networks. In particular, RMDS only exploits the local knowledge of a particular node to compute the multicast tree, which significantly reduces the signalling overhead in comparison with network layer and overlay solutions. Simulation results elucidate that RMDS optimizes resources' allocation by reducing significantly the network load, the media access delay and the data drop rate compared to the classical approach, which is based on the combination of spanning tree algorithm and IGMP snooping protocol.

The increased number and diversity of underlying networks have made transparent network migration a necessity. Through its support for multi-homing the Stream Control Transmission Protocol (SCTP) enables seamless network mobility by abstracting multiple underlying physical paths into a single end-to-end association. One of these paths is selected as the primary. When a number of retransmission failures occur on the primary path, switchover is initiated to a secondary path. The number of retransmission attempts before switchover is initiated can be configured; however, the delay between each retransmission is managed internally in SCTP using a Retransmission TimeOut (RTO) value. This paper shows that the current SCTP mechanism for calculating RTO values is inappropriate in WLAN environments, since increased Round Trip Times (RTT) significantly distort RTO calculations. Experimental and simulated results indicate that SCTP behaves in a counterintuitive manner which allows more time for switchover as network conditions degrade: delays of up to 187 seconds can be experienced before switchover occurs. We show that additional SCTP parameters need to be carefully configured in order to reduce this switchover delay to a more acceptable level.

In this paper, a problem formulation for determining optimal node location for base stations (BSs) and relay stations (RSs) in relay-based 802.16 networks is developed. The formulation results in an Integer Programming problem. A small modification to the original model is also considered in which the state space is reduced by limiting which nodes can be associated with which. Standard branch and bound techniques are used to solve the problem. The key findings of the paper are that standard techniques can be used to find solutions to problems of small metropolitan scale or for areas within a larger city.

In this paper, a clustering approach to solve a network planning problem for 802.16J relay networks is considered. Our clustering approach consists of three basic steps: (1) divide the nodes into k distinct clusters, (2) solve the planning problem separately for each cluster, and (3) perform a final optimization to reduce issues arising at cluster boundaries. Simulation results show that our approach is more efficient than existing approaches: solutions of equivalent quality can be found in 40% of the time. Thus our technique can be used to solve larger problems with similar hardware, or similar size problems in less time.

The performance of multi-homed transport protocols tolerant of network failure is studied. It evaluates the performance of different retransmission policies combined with path failure detection thresholds, infinite or finite receive buffers for various path bandwidths, delays and loss rate conditions through stream control transmission protocol simulation. The results show that retransmission policies perform differently with different path failure detection threshold configurations. It identifies that retransmission of all data on an alternate path with the path failure detection threshold set to zero performs the best in symmetric path conditions but its performance degrades acutely in asymmetric path conditions even when the alternate path delay is shorter than the primary path delay. It illustrates that retransmission of all data on the same path with the path failure detection threshold set to one or zero gives the most stable performance in all path configurations.

An approach to mitigating interference between 802.16 license-exempt systems is proposed in this paper. More specifically, the approach focuses on solving problems which arise when two or more 802.16 systems operate on the same channel in close proximity to each other. The essence of the approach is a distributed mechanism which can apportion the available OFDM subcarriers between the different 802.16 systems. Simulation results show that the topology and the distributions of base stations (BSs) and the subscriber stations (SSs) have a significant impact on the system performance. Also, the system is very sensitive to the order in which the different nodes in the system are activated. Furthermore, the system with the given parameters can operate satisfactorily for up to 6 BSs in the same area, but scalability problems arise if more BSs are added.

In this paper a scheme is proposed to deal with congestion problems that can arise due to Link Adaptation (LA) in Wireless Local Area Networks (WLANs) in the presence of VoIP traffic. The proposed scheme operates by first determining if LA has resulted in the system becoming congested. If not, no further action is taken. However, if, LA has resulted in an overloaded system, the voice codec of the handset which has undergone LA is adapted so as to restore the system to its earlier state, thereby alleviating the congestion. This is achieved by specifically adapting the codec so as to maintain approximately the same level of medium usage as was used prior to the LA. The proposed scheme was evaluated on an experimental test-bed and results show that the codec adaptation was very effective at overcoming the problem of LA.

The seamless handover of streamed video in a WLAN with UDP as the transport layer is considered. The use of handover for stationary nodes in the case of network congestion is motivated. Next, the relationship between delay and loss in WLANs is studied, with the conclusion that delay can be used as an indicator of when loss is likely to occur. Delay can therefore be used as a basis of a handover scheme which can minimize loss. Such a handover scheme is proposed in which the client makes two simultaneous connections to the same server through two separate WLANs, and it is shown that the client can use the relative packet delay between the two streams to determine which network delivers the best performance; this information is then used to determine when to perform a handover. The proposed scheme is implemented and results are presented that show the successful handover of an RTP over UDP stream using this scheme in a live WLAN environment.

A study of the performance of a number of different multiplexing schemes was conducted in the context of streaming of MPEG-4 object-based content, with particular emphasis on streaming content to mobile devices. The comparison involved six different schemes. The schemes differed in terms of how they packed the data for each arbitrarily shaped video object into packets. An experimental testbed was constructed to compare the performance of the different schemes. The experiments showed that the scheme in which no effort is made to maximise the amount of data in the packet performs worse than the others in terms of the amount of overhead it generates and the video quality obtained when it is used to stream content. The other schemes did exhibit small differences in terms of the amount of overhead generated and video quality obtained, but the differences were not sufficiently large to be able to identify any as being clearly better than the others.

This work describes a detailed simulation-based study of the performance of an IEEE 802.11e Medium Access Control (MAC) layer over an IEEE 802.11g Physical (PHY) layer. The study focuses on the number of simultaneous bidirectional G.711 Voice over IP (VoIP) calls that can be supported by a Wireless Local Area Network (WLAN) using the Extended Rate PHY - Orthogonal Frequency Division Modulation (ERP-OFDM) mode of 802.11g.A new scheme for adapting the WLAN MAC parameters is proposed in this work. The new scheme dynamically adapts the Contention Window (CW) based on the retransmission rate of the system. In addition, an adaptive Transmission Opportunity (TXOP) mechanism aids in balancing the uplink and downlink traffic levels and so provides the equality in uplink and downlink performance that is required for bidirectional VoIP traffic. The proposed scheme can thus maintain acceptable levels of QoS for higher call capacities, increasing the overall VoIP capacity of the system.

This article presents objective and subjective testing results that assess the performance of the Quality-Oriented Adaptation Scheme (QOAS) when used for high quality multimedia streaming over local broadband IP networks. Results of objective tests using a QOAS simulation model show very efficient adaptation in terms of end-user perceived quality, loss rate, and bandwidth utilization, compared to existing adaptive streaming schemes such as LDA+, and TFRCP. Subjective tests confirm these results by showing high end-user perceived quality of the QOAS under various network conditions.

Many adaptive delivery mechanisms have been devised for streaming multimedia over best-effort IP networks, such as the Internet. Most of these adaptive schemes do not consider the user's perception of quality when making adaptations. We describe a perceptual quality adaptation algorithm (PQA) and prototype system architecture that uses knowledge of user perceived quality to make adaptation decisions using an optimum adaptation trajectory. This optimum adaptation trajectory indicates how encoding quality should be adapted (upgraded/downgraded) with respect to user perceived quality in response to rapidly fluctuating network conditions. We present simulation results that demonstrate the behavior of a perceptual quality adaptation algorithm.

Delivering PSTN-like quality over current best-effort Internet infrastructure presents many technical challenges. Much research has focused on receiver-based approaches, which adapt to varying network conditions in order to optimize playout quality. In this paper, we propose and evaluate a receiver-based approach that implements a hybrid adaptive-fixed playout regime by integrating synchronized time into the playout algorithm. Such as approach can deliver significantly better quality than existing adaptive techniques particularly when the underlying network is not heavily congested and end-to-end delays are not excessive. We present some initial results form our testbed system using the ITU-T E-model to quantify improvement.

The circuit switched POTS (plain old telephone system) preserves the timing relationship between media samples from sender to receiver through use of a common clock. For PC-based Internet multimedia, the existence of separate audio and system clocks on either end-host can introduce significant complications. Much work has taken place in recent years that addresses the issue of system clock skew and its effect on precise delay measurement. In a voice over IP (VoIP) environment, where adaptive buffering techniques are employed, system and audio clock skew can distort both delay measurement and playout control as well as lead to poor buffer performance. This paper presents a high level mechanism to measure and compensate for the skew relationships between system and audio clocks at each end of a multimedia session. The mechanism utilises both the network time protocol (NTP) and the RTP (realtime transport protocol) control protocol or RTCP. Preliminary and positive results are presented from a testbed system and plans for further work are outlined.

Many adaptive delivery mechanisms have been devised for streaming multimedia over best-effort IP networks. Most of these adaptive schemes do not consider the user's perception of quality when making adaptations. We propose that an optimum adaptation trajectory exists which indicates how encoding quality should be adapted (upgraded/downgraded) with respect to user perceived quality in response to network conditions. This optimum adaptation trajectory can be used with any transmission adaptation policy. We describe a system architecture that uses knowledge of user perceived quality to make adaptation decisions and give an example of how this knowledge can be used to complement the sender-based adaptation algorithm, LDA.

Lately, multimedia-related Internet applications have become very popular, and make up an increasing percentage of network traffic. This paper presents a quality-of-transmission-orientated adaptive mechanism for streaming of pre-recorded multimedia content. It aims at maintaining the continuity of both the transmission and the remote stream play-out, at the expense of varying the stream's quality. A feedback scheme, in conjunction with a quality of transmission grading scheme, allows the server to learn the current network conditions. During transmission, the server can switch between different quality versions of the same multimedia content at certain checkpoints to modify the quality of the overall streaming process, and therefore the transferred quantity of data. Preliminary statistical and user perceptual test results from our prototype system show that by using our adaptive mechanism in increased traffic conditions, the users' satisfaction was higher than if a receiver buffering solution was used.

Currently multimedia is either downloaded before viewing, or streamed over a network. However, the problem of streaming real-time or near real-time applications with a specified quality of service (QoS) over the Internet is still unsolved. The Real-time Transport Protocol (RTP) can be used to facilitate streaming, but also has the potential to support QoS. By gathering network statistics during the session and defining different QoS levels, we propose to adapt multimedia streaming to a fluctuating network load and/or client requests, thereby providing adaptive QoS. We describe the simple server and client applications we have implemented to illustrate this adaptation process.

This paper presents a prototype computer supported cooperative work (CSCW) environment that supports the engineering design process. In particular, this environment provides collaborative tools that support computer-aided design (CAD) and computer-aided software engineering (CASE). This paper takes an high level look at the system as a whole and then focuses on the method used to implement the CASE support. It addresses how group members can simultaneously work on coding a program and then integrate their work to form a single program inside this environment. © 1998 John Wiley & Sons, Ltd.

For MPP's to solve new and interesting problems, they must support ihe development of sophisticated algorithms on very large data sets.Successful development depends strongly on the speed of the execute-fix cycle.Sequential machines cannot provide suflciently fast execution of large problems, but many programming systems available on MPP's ;!s date appear, and w+iceis given that copying is by permission of the Asmciation for Compuing Macbkuxy.To copy &envise, or to repubhsb, quires a fee sndor specific prmiskm.