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In this paper, the predefined-time cooperative platoon control problem with constrained communication range for uncertain networked aerial vehicles is considered. The uncertain networked aerial vehicles are subjected to external disturbance and parameter uncertainties. A novel adaptive sliding mode disturbance observer is first designed for single uncertain networked aerial vehicle with an RBFNN estimator to guarantee the control performance. By embedding a dynamic control gain associated with the predefined convergence time, the proposed disturbance observer is proved to be uniformly ultimate boundedness (UUB) stable by the time transformation approach. Then the dynamic gain technology is combined with the prescribed performance control to design the platoon controllers for uncertain networked aerial vehicles. With the proposed disturbance observer and the distribute controller, the platoon can be achieved within the predefined time. The proposed approach can simultaneously guarantee the system stabile without any initial conditions and system parameters. Finally, some simulation experiments are given to verify the effectiveness of the proposed protocols.

Indoor positioning plays an important role in a variety of applications under Internet of Things (IoT). Conventional WiFi fingerprinting-based indoor positioning systems (IPSs) usually require extensive manual calibrations to construct radio maps. This process severely limits the system scalability and adaptiveness. Pedestrian dead reckoning (PDR) is a popular method that can avoid the calibration process. However, PDR-based IPSs typically suffer from accumulated errors. To tackle this problem, many refinement methods require map information or floorplans which may not be available or up-to-date in practice. With the development of IoT, various types of crowdsourced data become available. In this work, we propose GraphIPS, a calibration-free and map-free IPS which dynamically generates accurate radio maps by utilizing smartphone crowdsourced WiFi and inertial measurement unit (IMU) data. GraphIPS fuses the crowdsourced data into a graph-based formulation and applies the multidimensional scaling (MDS) algorithm to compute the positions of the user’s steps. The experimental results show that GraphIPS achieves comparable accuracy to the calibration-based method in a significantly shorter run time than optimization-based methods. In addition to smartphones, GraphIPS is also potentially applicable for the smart wearables with embedded WiFi modules and IMUs.

The platoon control for vehicles can efficiently reduce traffic pressure. Current control schemes are able to achieve stable platoon control, but cannot guarantee collision avoidance, connectivity preservation and convergence time at the same time. In this paper, we propose a novel control scheme that can simultaneously guarantee the safe distance and communication connectivity, which is called flexible safe distance constraint, and also can guarantee the specified convergence time. A dynamic gain based distributed control law is first designed for the vehicle with single-integral model. Using the prescribed transient and steady-state performance control approach, the flexible safe distance constraint can be satisfied. Using the time transformation method and Lyapunov stability theory, the closed-loop systems under the proposed protocols can achieve stable platoon within the specified time. Compared with some existing results, the novelty of this work is that the proposed approaches allow a vehicle to converge with the platoon within any preset time without dependence on the initial conditions or system parameters. Another contribution of this work is to propose specified-time platoon control protocols for the vehicle with double-integral model under a flexible safe distance constraint. Furthermore, in order to get closer to the actual system, the controller is extended to the triple-integral system, and some special cases are also discussed. Finally, some simulations are presented to show the effectiveness of the proposed protocols.

Privacy-preserving routing protocols in wireless networks frequently utilize additional artificial traffic to hide the identities of communicating source-destination pairs. Usually, the addition of artificial traffic is done heuristically with no guarantees that the transmission cost, latency, and so on, are optimized in every network topology. In this paper, we explicitly examine the privacy-utility tradeoff problem for wireless networks and develop a novel privacy-preserving routing algorithm called optimal privacy enhancing routing algorithm (OPERA). OPERA uses a statistical decision-making framework to optimize the privacy of the routing protocol given a utility (or cost) constraint. We consider global adversaries with both lossless and lossy observations that use the Bayesian maximum-a-posteriori (MAP) estimation strategy. We formulate the privacy-utility tradeoff problem as a linear program, which can be efficiently solved. Our simulation results demonstrate that OPERA reduces the adversary’s detection probability by up to 50% compared to the random Uniform and Greedy heuristics, and up to five times compared to a baseline scheme. In addition, OPERA also outperforms the conventional information-theoretic mutual information approach.

We develop a new location spoofing detection algorithm for geo-spatial tagging and location-based services in the Internet of Things (IoT), called Enhanced Location Spoofing Detection using Audibility (ELSA) which can be implemented at the backend server without modifying existing legacy IoT systems. ELSA is based on a statistical decision theory framework and uses two-way time-of-arrival (TW-TOA) information between the user's device and the anchors. In addition to the TW-TOA information, ELSA exploits the implicit available audibility information to improve detection rates of location spoofing attacks. Given TW-TOA and audibility information, we derive the decision rule for the verification of the device's location, based on the generalized likelihood ratio test. We develop a practical threat model for delay measurements spoofing scenarios, and investigate in detail the performance of ELSA in terms of detection and false alarm rates. Our extensive simulation results on both synthetic and real-world datasets demonstrate the superior performance of ELSA compared to conventional non-audibility-aware approaches., Comment: A shorten version of this work has been accepted to the IEEE IoT Journal (IoT-J) on 08-Feb-2016

This paper uses a spatial Aloha model to describe a distributed autonomous wireless network in which a group of transmit-receive pairs (users) shares a common collision channel via slotted-Aloha-like random access. The objective of this study is to develop an intelligent algorithm to be embedded into the transceivers so that all users know how to self-tune their medium access probability (MAP) to achieve overall Pareto optimality in terms of network throughput under spatial reuse while maintaining network stability. While the optimal solution requires each user to have complete information about the network, our proposed algorithm only requires users to have local information. The fundamental of our algorithm is that the users will first self-organize into a number of non-overlapping neighborhoods, and the user with the maximum node degree in each neighborhood is elected as the local leader (LL). Each LL then adjusts its MAP according to a parameter R which indicates the radio intensity level in its neighboring region, whereas the remaining users in the neighborhood simply follow the same MAP value. We show that by ensuring R less than or equal to 2 at the LLs, the stability of the entire network can be assured even when each user only has partial network information. For practical implementation, we propose each LL to use R=2 as the constant reference signal to its built-in proportional and integral controller. The settings of the control parameters are discussed and we validate through simulations that the proposed method is able to achieve close-to-Pareto-front throughput., 32 pages, 10 figures, accepted for publication in IEEE Transactions on Vehicular Technology

Inter-user interference occurs when multiple body sensor networks (BSNs) are transmitting simultaneously in close proximity to each other. Interference analysis in BSNs is challenging due to the hybrid medium access control (MAC) and the specific channel characteristics of BSNs. This paper presents a stochastic geometry analysis framework for inter-user interference in IEEE 802.15.6 BSNs. An extended Matern point process is proposed to model the complex spatial distribution of the interfering BSNs caused by the hybrid MAC defined in IEEE 802.15.6. We employ stochastic geometry approach to evaluate the performance of BSNs, considering the specific channel characteristics of BSNs in the vicinity of human body. Performance metrics are derived in terms of outage probability and spatial throughput in the presence of inter-user interference. We conduct performance evaluation through extensive simulations and show that the simulation results fit well with the analytic results. Insights are provided on the determination of the interference detection range, the BSN density, and the design of MAC for BSNs.

Mobile ad hoc networks (MANETs) contain individual nodes exchanging data in a distributed manner. Although each node is capable of determining its own transmission power level, rate adaptation method and routing strategy, few existing routing protocols fully explore the potential performance improvement by the joint optimization of power, rate and routing. This paper proposes and evaluates a cross-layer routing protocol considering power control and rate adaptation by using a delay-based non-selfish cost function with a multi-agent Q-learning coordination mechanism. A simulation-based evaluation, considering node density, node mobility, traffic load and flow number, shows that our algorithm improves the average end-to-end latency and throughput with acceptable power consumption level.

We contend that context information of Internet clients can help to efficiently manage a variety of underlying resources for different Internet services and systems. We therefore propose a resource distribution framework that provides quality of experience (QoE) aware service differentiation, which means that starving clients are prioritized in resource allocation to enhance the corresponding end-user's QoE. The framework also actively motivates each Internet client to consistently provide its actual context information and to adopt moderate competition policies, given that all clients are selfish but rational in nature. We analyze the Internet client's behavior by formulating a non-cooperative game and prove that the framework guides all clients (game players) towards a unique Nash equilibrium. Furthermore, we prove that the distribution results computed by the framework maximize a social welfare function. Throughout this paper, we demonstrate the motivation, operation and performance of the framework by presenting a Web system example, which leverages on the advanced context information deduced by a context-aware system.

Dynamic spectrum access has gained traction in wireless sensor networks (WSNs) because of the scarcity in spectrum caused by the proliferation of wireless devices and services, and it provides spectrum efficient communication for the WSNs. However, the communication between nodes in a cognitive radio sensor network (CRSN) is affected by the transmission power, fading, and interference with licensed users, and these factors hinder the data transmission between the energy constrained cognitive radio sensor nodes. Therefore, there is a need for an adaptive energy-efficient optimization scheme which takes into account the varying environment conditions. Since packet length plays a pivotal role in determining the performance of the network, packet size adaptation that is aware of the channel characteristics may bring about performance improvement. Furthermore, existing packet size optimization or channel selection schemes devised for WSNs and CR networks are not appropriate for the CRSN framework. In this paper, we devise a dynamic packet size optimization and channel selection scheme (DyPSOCS) for CRSNs. We employ a constrained Markov decision process (CMDP) to solve the optimization problem with quality of service (QoS) constraints. Simulation results show improvement in QoS performance as well as energy efficiency when compared to other schemes.

The wireless multihop backhaul is a unique feature of wireless mesh networks (WMNs), which necessitates redesign of association control algorithms. In this paper, we formulate and propose approximation algorithms for the problem of optimal joint association and bandwidth allocation in WMNs, considering max–min fairness (MM) and proportional fairness (PF) objectives. We first relax the integral association constraint and get an optimal fractional association solution. Then, we propose two rounding algorithms, namely, largest fraction rounding and bipartite graph rounding, to get an integral solution and analyze their theoretical approximation ratios. Finally, we propose two approximation ratio improvement algorithms so that the improved approximation ratio can more accurately reflect the true performance gap between the produced solution and the optimal one. Our simulation results show that the proposed algorithms achieve performance that is close to the optimal and outperform popular heuristic algorithms. We also compare the performance of PF and MM in WMNs in terms of network throughput and fairness in user bandwidth. Finally, we compare the performances of the proposed rounding algorithms and show that the approximation ratio can be reduced to 1–2 by the proposed ratio improvement algorithms. Therefore, our proposed algorithm is able to achieve nearly optimal association control, as well as bandwidth allocation, considering MM or PF, with small approximation ratios, in WMNs.

Network coding techniques are usually applied upon network-layer protocols to improve throughput in wireless networks. In scenarios with multiple unicast sessions, fairness is also an important factor. Therefore, a network coding-aware packet-scheduling algorithm is required. A packet-scheduling algorithm determines which packet to send next from a node’s packet backlog. Existing protocols mostly employ a basic round-robin scheduling algorithm to give “equal” opportunities to different packet flows. In fact, this “equal”-opportunity scheduling is neither fair, nor efficient. This paper intends to accentuate the importance of a coding-aware scheduling scheme. With a good scheduling scheme, we can gain more control over the per-flow throughput and fairness. Specifically, we first formulate a static scheduling problem and propose an algorithm to find the optimal scheduling scheme. We then extend the technique to a dynamic setting and, later, to practical routing protocols. Results show that the algorithm is comparatively scalable, and it can improve the throughput gain when the network is not severely saturated. The fairness among flows is drastically improved as a result of this scheduling scheme.

Step counting-based dead-reckoning has been widely accepted as a cheap and effective solution for indoor pedestrian tracking using a hand-held device equipped with motion sensors. To compensate for the accumulating error in a dead-reckoning tracking system, extra techniques are always fused together to form a hybrid system. In this paper, we first propose a map matching (MM) enhanced particle filter (PF) as a robust localization solution, in which MM utilizes the corridor information to calibrate the step direction estimation and PF is applied to filter out impossible locations. To overcome the dependency on manually input corridor information in the MM algorithm, as well as the computational complexity in combining two such algorithms, an improved PF is proposed. By better modelling of the location error, the improved PF calibrates the location estimation, as well as step direction estimation when the map information is available, while keeping the computational complexity the same as the original PF. Experimental results show that in a quite dense map constraint environment with corridors, the proposed methods have similar accuracy, but outperform the original PF in terms of accuracy. When only partial map constraints are applied to simulate a new testbed, the improved PF obtains the most robust and accurate results. Therefore, the improved PF is the recommended DR solution, which is adaptive to various indoor environments.

There have been researchers working on the design of coding-aware routing protocols to exploit the power of network coding in static wireless ad hoc networks. However, most of them have overlooked the fact that routing decisions for multiple flows need to be coordinated in order to achieve maximum throughput. A mechanism to alter prior routing decisions is mandatory for this purpose. In this paper, we propose Self-recommendation coding-aware routing (SCAR), to provide such a mechanism. With intermediate nodes sensing the arrival of new flows, they can send self-recommendations to source nodes, triggering a route-change procedure. In the route-change procedure, adjustments are applied to the route metrics so that the newly recommended route can be fairly weighed without bias. A thorough analysis of coding structures is carried out, and a series of indicators are devised to predict how much throughput benefits we can gain from the mere knowledge of the topology. The rationale behind the protocol design and the effectiveness of the indicators are further justified by a series of simulations. Results show that SCAR can exploit coding opportunities better and provide higher throughput than other coding-aware routing protocols. It is also shown that the opportunity of throughput gain is ubiquitous and it is tested on many typical topologies.

Inter-user interference deteriorates reliable communication in body sensor networks (BSNs) when multiple BSNs are transmitting simultaneously in close proximity to each other. This paper presents a lightweight and distributed inter-user interference mitigation (IIM) scheme, that can be easily integrated with the IEEE 802.15.4 protocol stack. The proposed scheme takes into consideration the generic property of low channel utilization in BSNs and enables affected BSNs to adaptively reschedule their transmission time or switch channels. Based on the detected information from neighboring BSNs, BSNs reschedule their transmissions in a distributed and coordinated manner, so that wireless channels can be effectively utilized by multiple BSNs. Moreover, the IIM scheme is performed only when the performance of the BSN is degraded to an unacceptable level due to severe interference to reduce the rescheduling cost. Simulation results show that the proposed scheme improves the network throughput by 18% and reduces the energy consumption by 22% as compared with the existing beacon schedule scheme.

In this paper, we consider the medium access control (MAC) protocol design for random access cognitive radio network (CRN). Based on asynchronous spectrum sensing technique and RTS/CTS mechanism, a new MAC protocol, namely, cognitive-radio-based carrier sense medium access with collision avoidance (CR-CSMA/CA) is proposed to coordinate the channel access of secondary network as well as protect the operation of primary network, which applies to both single and multiple channel models. Using the G/G/1 queuing model with consideration of unsaturated and saturated network condition, we develop a framework to analyze the proposed MAC protocol and also derive closed-form expressions of specific performance metrics such as normalized throughput, average packet service time, etc. Performance evaluations illustrate and validate that the performance of CR-CSMA/CA varies with the offered traffic load of secondary network and the spectrum utilization rate of primary network, respectively, and also show that CR-CSMA/CA outperforms other relevant MAC protocols.

Existing approaches to indoor tracking have various limitations. Location-fingerprinting approaches are labor intensive and vulnerable to environmental changes. Trilateration approaches require at least three line-of-sight beacons for coverage at any point in the service area, which results in heavy infrastructure cost. Dead reckoning (DR) approaches rely on knowledge of the initial location and suffer from tracking error accumulation. Despite this, we adopt DR for location tracking because of the recent emergence of affordable hand-held devices equipped with low-cost DR-enabling sensors. In this paper, we propose an indoor pedestrian tracking system that comprises of a DR subsystem implemented on a mobile phone and a ranging subsystem with a sparse infrastructure. A particle-filter-based fusion scheme is applied to bound the accumulated tracking error by fusing DR with sparse range measurements. Experimental results show that the proposed system is able to track users much better than DR alone. The system is robust even when: 1) the initial user location is not available; 2) range updates are noisy; and 3) range updates are intermittent, both temporally and spatially.

We propose a novel algorithm to improve the accuracy in estimating the angle-of-arrival (AoA) when the MUSIC (MUltiple SIgnal Classification) algorithm is used. An optimal precoder, with the objective to minimize the estimation errors of the AoAs, is first derived. However, to compute the optimal precoder requires the channel side information at the transmitter (CSIT) exclusive of the receiver array, which cannot be separately estimated practically. A more practical precoder design approach, which leverages on the feedback CSIT estimated at the receiver, is next proposed. We demonstrate that the practical precoder performs closely to the optimal precoder through simulation, and both precoders exhibit considerable performance improvement compared with the AoA estimation without precoder. Furthermore, the precoder technique is applied to a known AoA-based localization method, and the improvement on the accuracy of the location estimate is studied.

Advances in Ambient Intelligence (AmI) technologies, when combined with user-centric computing, present major opportunities for building new communication pathways between end-users and traditional computer networks. We propose to explicitly take the end-user into account by defining a new functional module called the User Module across the layers of the Internet protocol stack. This new User Module empowers end-users to improve network performance and enhance the end-user Quality of Experience (QoE) based on their interaction activities. To successfully capture the significant interaction information of end-users, we leverage on the well-established Human Information Processing approach to build the end-user model. Subsequently, we present two exemplary User Module applications addressing the Hypertext Transfer Protocol (HTTP) and the Transmission Control Protocol (TCP), respectively. Both applications illustrate how the User Module operates to effectively improve the underlying network performance and eventually enhance the end-user QoE.

Context awareness, as one of the key techniques applied in ubiquitous computing, makes information technology invisible and seamless to people's daily living. As a result, numerous context frameworks have been developed for simplifying the development of context-aware applications by providing low-level context data operations such as acquisitions and simple aggregations in terms of APIs or toolkits. These frameworks are still falling short in requiring developers to explicitly deal with context-related tasks such as constraint enforcement in the application code. In this article, we present a framework to bridge the gap. More specifically, an application context model (ACM) is proposed for developers to specify their requirements on the context-related tasks. At application runtime, the ACM is instantiated for automatic context realization by the application context engine (ACE), which supports the full life cycle of each ACM instance (initialization, execution, and termination). We validate the concept of the framework through a case study, and present the experimental results based on the system prototype.

In this paper, we consider medium access control (MAC) protocol design for random-access cognitive radio (CR) networks. A two-level opportunistic spectrum access strategy is proposed to optimize the system performance of the secondary network and to adequately protect the operation of the primary network. At the first level, secondary users (SUs) maintain a sufficient detection probability to avoid interference with primary users (PUs), and the spectrum sensing time is optimized to control the total traffic rate of the secondary network allowed for random access when the channel is detected to be available. At the second level, two MAC protocols called the slotted cognitive radio ALOHA (CR-ALOHA) and cognitive-radio-based carrier-sensing multiple access (CR-CSMA) are developed to deal with the packet scheduling of the secondary network. We employ normalized throughput and average packet delay as the network metrics and derive closed-form expressions to evaluate the performance of the secondary network for our proposed protocols. Moreover, we use the interference and agility factors as the performance parameters to measure the protection effects on the primary network. For various frame lengths and numbers of SUs, the optimal performance of throughput and delay can be achieved at the same spectrum sensing time, and there also exists a tradeoff between the achievable performance of the secondary network and the effects of protection on the primary network. Simulation results show that the CR-CSMA protocol outperforms the slotted CR-ALOHA protocol and that the PUs' activities have an influence on the performance of SUs for both the slotted CR-ALOHA and CR-CSMA.

The problem of conserving energy under multiple constraints of query waiting delays and sensing coverage preservation in query-based wireless sensor networks is addressed. We propose a network architecture based on the cyclic symmetric block design class of wakeup schemes. Using a target tracking application as an example, specific requirements of the application translates to design parameters in our proposed solution. Our proposal demonstrates good delay performances, high target tracking accuracies and low target identification errors, without the need for costly double-radio channels while increasing network lifetimes by a factor of four to eight over traditional methods.

Energy is often identified as the single most important resource in wireless battery-powered sensor networks. While current wakeup schemes in the literature promise to conserve energy in such networks, they apply several assumptions that may not be always true. First, all applications are assumed to require sensing coverage and network connectivity continuously; Second, a random dense deployment of sensors is always assumed possible; And third, the sensing ranges can be easily modeled by some sensing circles. In this paper, we show that these assumptions are not always valid, and propose sensor node wakeup schemes based on combinatorics block design to address energy-related issues when common assumptions fail. Another distinguishing feature of our work is also the proposal of a dual wakeup design for sensing and communications as these are two very different tasks. Finally, we verified our proposed schemes with simulations and experiments.

In this paper, we present a system model for multiuser multicode code-division multiple access (CDMA) in a multipath fading channel and propose a hybrid receiver scheme for the system. Conventional receivers for CDMA systems utilized interference cancellation (IC) schemes, with the RAKE receiver as an initial data estimator. However, the RAKE receiver generates inaccurate data estimates due the interference that is caused by the cross correlation between the spreading codes. This inaccurate data estimate leads to significant error propagation to the subsequent stages and thus degrades the bit error rate (BER) performance. Our proposed scheme overcomes the problem by using a more accurate initial data estimator. It consists of an equalizer for obtaining initial data estimation, followed by several stages of parallel IC (PIC). Computer simulation results show that the BER curves of our proposed scheme do not encounter an error floor under all channel conditions; in contrast, the BER curves of the conventional RAKE-PIC receiver are constrained by an irreducible error floor. In addition, in an uplink four-path channel and at a BER of 10-3, our simulation results show that a one-stage PIC achieves a 2.5-dB gain over the first stage equalization receiver.

Energy awareness is a crucial component in the design of wireless sensor networks at all layers. This paper looks into efficient energy utilization of a target-tracking sensor network by predicting a target's trajectory through experience. While this is not new, the chief novelty comes in conserving energy through both dynamic spatial and temporal management of sensors while assuming minimal locality information. We adapted our target trajectory model from the Gauss-Markov mobility model, formulated the tracking problem as a hierarchical Markov decision process (HMDP), and solved it through neurodynamic programming. Our HMDP for target-tracking (HMTT) algorithm conserves energy by reducing the rate of sensing (temporal management) but maintains an acceptable tracking accuracy through trajectory prediction (spatial management) of multiple targets. We derived some theoretical bounds on accuracy and energy utilization of HMTT. Simulation results demonstrated the effectiveness of HMTT in energy conservation and tracking accuracy against two other predictive tracking algorithms, with accuracy of up to 47% higher and energy savings of up to 200%

This paper studies the performance of overlay device-to-device (D2D) communication links via carrier sense multiple access (CSMA) protocols. We assume that the D2D links have heterogeneous rate requirements and different willingness to pay, and each of them acts non-altruistically to achieve its target rate while maximizing its own payoff. Spatial reuse is allowed if the links are not interfering with each other. A non-cooperative game model is used to address the resource allocation among the D2D links, at the same time leveraging on the ideal CSMA network (ICN) model to address the physical channel access issue. We propose a Stackelberg game in which the base station in the cellular network acts as a Stackelberg leader to regulate the individual payoff by modifying the unit service price so that the total D2D throughput is maximized. The problem is shown to be quasi-convex and can be solved by a sequence of equivalent convex optimization problems. The pricing strategies are designed so that the network always operates within the feasible throughput region. The results are verified by simulations., 32 pages, 11 figures, accepted for publication in IEEE Transactions on Vehicular Technology, Dec 11, 2015

This paper proposes a new video distribution service: Video-In-Network (VIN). In VIN, videos are continuously circulating in an optical network where they can be easily retrieved by VIN Nodes. A mathematical model of the VIN system was derived and used to explore the performance of VIN in terms of the maximum number of concurrent video streams which can be supported by the system. We then compared VIN with Staggered Multicast. We found that VIN has a number of advantages over Staggered Multicast. First, VIN is more scalable in terms of the number of streams/channels. Second, the startup latency of VIN is shorter than that of Staggered Multicast. Third, Staggered Multicast is a near-VOD system and the video clients usually have no specific channels to the server to request for video. In the VIN system, the video clients can request the VIN Node for particular videos for multicast or unicast on demand.

Our analysis and simulations show that in a practical ATM network environment consisting of a mix of low cost ABR binary switches and higher cost ABR ERICA (explicit rate) switches, partially compliant ABR sources can illegally grab more bandwidth from the network without being detected. Consequently, fully compliant ABR sources lose their available fair share. At the same time, congestion conditions are experienced at the binary switches. Three schemes are contributed, namely SDP (partial-behaving user detection and punishment), DFC (Direct Fairness Control) and IFC (Instantaneous Fairness Control), all of which can be implemented in any ERICA switches with negligible increase in complexity, to overcome ABR source misbehaviour. Of the three, the IFC scheme is the most promising in terms of restoring fair share and reducing congestion in the binary switches.

Advance object oriented computing platform such as the Common Object Request Broker Architecture (CORBA) provides a conducive and standardized framework for the development of distributed applications. Most of the off-the-shelf CORBA are implemented over legacy network transports and distributed processing platforms such as TCP/IP and RPC. They are not suitable for real-time applications due to their high processing overheads, and lack of features and mechanisms in supporting quality of service both at the network level and at the end-host level. To overcome this limitation we have designed and implemented a CORBA-based Real Time Stream Service (RTSS) that allows real-time streams to be managed through the ‘CORBA channel’ but by-passing the heavy CORBA protocol stacks. RTSS aims to achieve an integrated QOS framework that incorporates both host scheduling and end-to-end network-level QOS to better support the processing of distributed multimedia applications over ATM networks. For host scheduling, a novel scheme of frequency-based scheduling mechanism has been proposed to cope with dynamic CPU load condition. The scheme has been implemented for a stand-alone host and will be extended to the networked environment. At the network-level QOS, RTSS provides object-oriented application programming interfaces (APIs) which guarantee end-to-end QOS when operating directly over ATM adaptation layers. The benefits of RTSS for the development of real-time multimedia distributed applications are demonstrated through a number of experiments.

The greatest single factor in enhancing spectral efficiency of a network is the mass deployment of microcells. By this simple technique we can repeatedly and efficiently reuse the precious spectrum. The number of users a network can support is fundamentally dependent on the common air interface (CAI) over which users communicate. User capacity is dependent on many factors, but the cardinal ones are the amount of spectrum the regulators allocate, the size of the radio coverage area from a base station (BS), and the amount of interference a particular radio link can tolerate. In this article we are primarily concerned with the system aspects associated with the CAI. We focus on the critical importance of BS siting. Starting with existing large cells, we deliberate on the problems that might arise in siting BSs in three dimensional microcells, in order to consider suitable multiple access methods for future cellular environments. >

Various strategies to provide low-delay high-quality digital speech communications in a high-capacity wireless network are examined. Various multiple access schemes based on time-division and packet reservation are compared in terms of their statistical multiplexing capabilities, sensitivity to speech packet dropping, delay, robustness to lossy packet environments, and overhead efficiency. In particular, a low-delay multiple access scheme, called shared time-division duplexing (STDD) is proposed. This scheme allows both the uplink and downlink traffic to share a common channel, thereby achieving high statistical multiplexing gain even with a low population of simultaneous conversations. The authors also propose a choice of low delay, high quality speech coding and digital modulation systems based on adaptive DPCM, with QDPSK or pseudo-analog transmission (skewed DPSK), for use in conjunction with the STDD multiple access protocol. The choice of the alternative systems depends on required end-to-end delay, recovered speech quality and bandwidth efficiency. Typically, with a total capacity of 1 MBaud, 2 ms frame and 8 kBaud speech coding rate, low delay STDD is able to support 48 pairs of users compared to 38, 35, and 16 for TDMA with speech activity detection, basic TDMA and PRMA respectively. This corresponds to respective gains of 26%, 37% and 200%. >

The author examines the performance of a packet reservation multiple access (PRMA) protocol in a metropolitan microcellular radio environment using computer simulations. Call characteristics, mobility, and channel conditions have an impact on PRMA performance which is measured in terms of the average packet dropping rate per call. In order to maintain a reasonable level of service quality for calls in progress, teletraffic loading can be controlled by introducing a call setup queue and limiting the number of active subscribers. Call mobility is found to have a minor impact on PRMA performance. PRMA is also fairly robust against adverse channel conditions with a drop in performance of about 15% when the channel packet loss rate is less than 0.01. Performance comparisons to other protocols are also carried out. >

The author studies the performance of a high capacity metropolitan microcellular radio network using computer simulation. Packet reservation multiple access carriers are dynamically assigned or released depending on current teletraffic loading conditions. Significant performance improvements are obtained using a 2-stage costing strategy which attempts to balance call blocking probabilities against packet dropping rate, thereby leading to more efficient utilisation of channel resources. The author achieves 40 to 50% improvements over a fixed allocation scheme in terms of the blocking probability performance, by soft assigning carriers to the microcells and performing a 2-stage dynamic carrier allocation procedure based on a simple costing algorithm which attempts to pack co-carrier cells as closely as possible. >

In a metropolitan microcellular environment, the cell coverage zone can be highly irregular. Thus highly overlapping areas can result due to an attempt to achieve ubiquitous coverage. The authors propose a predictive load sharing (PLS) scheme to alleviate localised congestion by using the knowledge of users potentially entering and leaving a cell. They study the system in a linear bidirectional highway environment. Results show that load carried is increased and the handoff failure rate is lowered compared to the fixed channel assignment (FCA) scheme. A lower handoff failure rate is a desirable feature since the forced termination of an existing call can be very annoying to a user. >

The authors propose an ordered dynamic channel assignment with reassignment (ODCAR) scheme and study its performance in a highway microcellular radio environment where the microcells are shaped to segments of the highway. Channels are assigned on an ordered basis in conjunction with a minimax algorithm to provide high capacity and to alleviate worst case channel congestion in each microcell. Simulation results show significant performance improvements in terms of channel utilization and probability of call failure. The load sharing feature of this improved scheme is demonstrated in a highway microcellular radio network with an asymmetrical teletraffic load condition. The authors examine how load sharing is accomplished under such circumstances. >

This paper describes the hardware implementation of Segnet, a bus network based on the CSMA/CD medium access control technique having dynamic segmentation capability. A six-station PC-based network was set up and its performance evaluated. The experimental results obtained are compared with the simulation results; excellent agreement is achieved. It is also found that Segnet performs better under clustered traffic environments and as the number of clusters increases. The performance of individual source-destination pairs is also investigated and the effect of varying packet length examined.

The performance of a dynamically segmentable ring network (R-Segnet) based on the CSMA/CD local area network protocol is studied in this paper. Two routing algorithms for the bidirectional rign are considered. The first transmits a packet in either direction with equal probability while the secons always sends a packet via the shortest path to its destination. Throughput and delay performance comparisons are made against CSMA/CD and against a linear version of this segmentable network (Segnet). These comparisons are conducted for both clustered and nonclustered traffic patterns within the network. The results show that in all cases R-Segnet performs significantly better than conventional CSMA/CD. In the random-destination random-routing case, the performance of R-Segnet is almost similar to that of linear Segnet. When shortest-path routing is used, R-Segnet is shown to be clearly superior. The performance gains are also shown to be shared equitably by all stations in R-Segnet.

The teletraffic performance of a highway microcellular digital mobile radio system having an oversailing macrocell that spans many microcells is presented. The microcellular cluster is composed of concatenated segments of the highway where each segment is a microcell, typically 500-2000 m in length, with the base stations located at lamp-post elevations. A narrowband time-division-multiple-access arrangement supporting ten channels per carrier and one carrier per base station is used. The teletraffic analysis assumes there are n-up and n-down lanes, and that the vehicular speeds conform to a truncated Gaussian distribution whose mean speed is 100 or 50 km/h when the vehicular traffic is free-flowing or in traffic-congested conditions, respectively. >