Metaverse-enabled learning is an immersive educational method blending virtual elements and real-world environments. This paper adopts a 6C model-based framework to analyze how inclusiveness, interactivity, and adaptability can be improved in learning environments through metaverse-enabled learning. Vision Pro is used as the core platform of the framework to incorporate several technologies, such as eye-tracking, spatial interaction, and virtual avatars. With these advanced technologies, the framework creates an accessible and engaging learning environment. A case study of a student competition demonstrates the framework’s practical application in developing Vision Pro applications. The 6C model-based framework guides the design and enhancement of these applications to promote a transformative and inclusive metaverse-enabled educational ecosystem.

UWB is becoming increasingly more available to the general public as part of consumer devices such as smartphones and smartwatches. This opens opportunities for new indoor positioning paradigms because UWB in consumer devices not only supports ranging but also AoA (Angle of Arrival) estimation, meaning dependence on additional positioning infrastructure can be reduced. Since this is a recent development, however, not much research has been conducted on evaluating UWB performance in these consumer devices and how to improve it for better indoor positioning accuracy. To contribute to this research gap, this paper is the first to propose a machine learning solution to AoA accuracy improvement in UWB-equipped iPhones when communicating with DWM3001CDK sensors while in motion. The distinguishing feature of our solution is that, unlike previous works, it uses AoA measurements for training instead of raw CIR (Channel Impulse Response) data, meaning the anchors do not need to be attached to a computer for data collection, which makes the installation of anchors more convenient. In addition, our solution combines machine learning with a collaborative approach based on our positioning vector framework, which further improves AoA error. We compiled a training dataset based on real UWB measurements collected in a large indoor environment. Extensive experiments were conducted to evaluate different machine learning models, and our results show that machine learning can improve the 90th percentile AoA error from about 60° to 11° and thus improve the average direction estimation accuracy to 96.85%.

We address the challenge of creating seamless, visually coherent 3D scenes from text descriptions and images, a task that is frequently hindered by sudden transitions, boundary artifacts, and inconsistent depth representations in current techniques. These issues not only disrupt the realism but also worsen as the scene scales up, resulting in poor quality for large-scale scene generation. To overcome these challenges, we present ArtArchitect, an innovative framework that introduces two main advancements. First, an enhanced Outpaint Modulator utilizes channel-aware noise thresholding to ensure smooth transitions, reduce boundary artifacts, and maintain fine details. Second, an Adaptive Depth Modulator combines adaptive window-based depth filling with edge-preserving smoothing to generate consistent depth maps and preserve geometric stability across different views. Our method effectively addresses common artifacts, enabling the creation of high-quality, large-scale 3D environments with strong spatial and visual continuity. Both qualitative and quantitative evaluations show that ArtArchitect significantly outperforms existing methods, setting a new benchmark for stable, immersive, and visually impressive 3D scene generation (Project page).

As an extension to a previous paper, a 4C model-based framework is presented in this short paper for hybrid teaching. The framework comprises three layers: model layer, platform layer and activity layer together with other supporting functions. Various methods are presented based on this framework, including 2D metaverse-based teaching, 3D metaverse-based teaching, teaching using a 360-degree camera with virtual reality support, meeting using a hybrid meeting camera and attending lectures using a telepresence robot. Furthermore, as a supporting function, online student eye movement can be analyzed using eye trackers. The aforementioned methods can provide valuable insights and also useful ideas for further research.

Open educational resources (OERs) can provide useful online materials to facilitate teaching and learning. It is desirable to provide a focused list for the global computing education community. In this short paper, we present the top 10 computer science OERs based on voting, as organized by the MERLOT Computer Science Editorial Board. These OERs cover various important computing topics, including general computing topics, programming, algorithms, machine learning etc. They provide good references for instructors to complement their lectures and strengthen student computing backgrounds.

Despite its high ranging accuracy and secure peer-to-peer ranging, UWB (ultrawide-band) has not been as widely adopted for indoor positioning as other radio technologies, such as WiFi and BLE (Bluetooth Low Energy), due to their high availability. However, UWB chips have recently started to be embedded in consumer devices like smartphones and can often support AoA (Angle of Arrival) estimation, which can aid in the positioning process. To contribute to the emerging research on UWB performance in different chips, this paper presents experimental results on UWB distance and relative angle estimation accuracy over time in UWB-equipped iPhones and a DWM3001CDK chip. iPhones were found to generally display better ranging performance, which declined in mobile scenarios. The UWB developments open new avenues of research for UWB- based collaborative indoor positioning that can reduce dependence on infrastructure, so this paper also proposes a novel dynamic positioning vector framework for mobile UWB-equipped (ultrawide-band) devices, along with new collaborative positioning methods based on the framework. Simulations on the framework's efficacy showed that the new methods can increase positioning coverage to 80% and halve positioning error.

This research proposes a dynamic resource allocation method for vehicle-to-everything (V2X) communications in the sixth generation (6G) cellular networks. Cellular V2X (C-V2X) communications empower advanced applications but at the same time bring unprecedented challenges in how to fully utilize the limited physical-layer resources, given the fact that most of the applications require both ultra low latency, high-data rate and high reliability. Resource allocation plays a pivotal role to satisfy such requirements as well as guarantee Quality of Service (QoS). Based on this observation, a novel fuzzy-logic-assisted$Q$learning (FAQ) model is proposed to intelligently and dynamically allocate resources by taking advantage of the centralized allocation mode. The proposed FAQ model reuses the resources to maximize the network throughput while minimizing the interference caused by concurrent transmissions. The fuzzy-logic module expedites the learning and improves the performance of the$Q$-learning. A mathematical model is developed to analyze the network throughput considering the interference. To evaluate the performance, a system model for V2X communications is built for urban areas, where various V2X services are deployed in the network. Simulation results show that the proposed FAQ algorithm can significantly outperform deep reinforcement learning,$Q$-learning and other advanced allocation strategies regarding the convergence speed and the network throughput.

Searchable encryption is a technique that can support operations on encrypted data directly. However, searchable encryption is still vulnerable to attacks that exploit the leakages from encrypted query results. This article presents an effective multi-server searchable encryption scheme to prevent volume and access pattern leakages. To hide the volume leakage of a keyword, a new index construction is proposed to compress multiple results into one index. To prevent the attacker from observing the access pattern of injected records, the update and search phases are executed in batches, such that the server can only retrieve multiple numbers of fixed volumes. To reduce the co-occurrence leakage, we propose our index distribution algorithm. Both records and queries are dispatched among cloud servers such that the attacker cannot recover the trapdoor values by only observing one cloud server. We use the minimum$s-t$cut algorithm to find the optimal assignment strategy that can diminish the query response time and the information disclosure at the same time. We formally analyze the security strengths and conduct evaluations. The experimental results indicate that our designs can strike a good balance between security and efficiency.

In recent years, there has been considerable interest in FinTech. One of the most popular research areas in FinTech is related to stock market analysis in general and stock price prediction in particular. In collaboration with the industry, this paper introduces an innovative concept called "Hybrid Intelligence" (HI), which aims to combine human intelligence and artificial/machine intelligence. We present our ongoing work with current results from the HI project. First, we present the HI website we are developing and some interesting data analytics for the Hong Kong stock market. In particular, we discuss interesting findings on the effectiveness of some technical indicators based on the Hong Kong stock market. Second, we present an AI model to predict the Hong Kong Hang Seng Index (HSI) on a weekly basis. Furthermore, the predictions can be enhanced by means of hybrid intelligence, taking into consideration the weekly voting of financial analysts in Hong Kong. Last but not least, we further discuss hybrid intelligence by using an AI model to predict the stock prices of stocks recommended by financial analysts in Hong Kong.

Hybrid/online teaching in general and HyFlex teaching in particular are now widely adopted among higher education institutions around the world due to their hybrid (physical/virtual) advantage and flexible arrangement. To gain a better understanding of hybrid/online teaching, we have conducted a survey at the International Conference on Teaching, Assessment and Learning for Engineering (TALE) 2022, one of the flagship conferences of the IEEE Education Society (i.e., for international conference participants from more than 16 countries/cities/regions). The aim is to evaluate hybrid/online teaching in general and the 4C elements (Content, Collaboration, Community and Communication) of a hybrid/online classroom model. Results from this international survey provide valuable insights, perspectives and good practices, and point to future research directions on this important topic.

202311 bcch

With the advent of Bluetooth low-energy (BLE)-enabled smartphones, there has been considerable interest in investigating BLE-based distancing/positioning methods (e.g., for social distancing applications). In this article, we present a novel hybrid learning method to support mobile ad-hoc distancing (MAD)/positioning (MAP) using BLE-enabled smartphones. Compared to traditional BLE-based distancing/positioning methods, the hybrid learning method provides the following unique features and contributions. First, it combines unsupervised learning, supervised learning, and genetic algorithms (GAs) for enhancing distance estimation accuracy. Second, unsupervised learning is employed to identify three pseudo channels/clusters for enhanced RSSI data processing. Third, its underlying mechanism is based on a new pattern-inspired approach to enhance the machine learning process. Fourth, it provides a flagging mechanism to alert users if a predicted distance is accurate or not. Fifth, it provides a model aggregation scheme with an innovative 2-D GA to aggregate the distance estimation results of different machine learning models. As an application of hybrid learning for distance estimation, we also present a new MAP scenario with an iterative algorithm to estimate mobile positions in an ad-hoc environment. Experimental results show the effectiveness of the hybrid learning method. In particular, hybrid learning without flagging and with flagging outperforms the baseline by 57% and 65%, respectively, in terms of mean absolute error. By means of model aggregation, a further 4% improvement can be realized. The hybrid learning approach can also be applied to previous work to enhance distance estimation accuracy and provide valuable insights for further research.

Applying peer-to-peer (P2P) architecture to online video games has already attracted both academic and industrial interests, since it removes the need for expensive server maintenance. However, there are two major issues preventing the use of a P2P architecture, namely how to provide an effective distributed data storage solution, and how to tackle potential cheating behaviors. Inspired by emerging blockchain techniques, we propose a novel consensus model called Proof-of-Play (PoP) to provide a decentralized data storage system that incorporates an anti-cheating mechanism for P2P games, by rewarding players that interact with the game as intended, along with consideration of security measures to address the Nothing-at-stake Problem and the Long-range Attack. To validate our design, we utilize a game-theory model to show that under certain assumptions, the integrity of the PoP system would not be undermined due to the best interests of any user. Then, as a proof-of-concept, we developed a P2P game ( Infinity Battle ) to demonstrate how a game can be integrated with PoP in practice. Finally, experiments were conducted to study PoP in comparison with Proof-of-Work (PoW) to show its advantages in various aspects.

This paper presents an experimental mobile app called Learning eGroup (LeG) for enhancing student communication and learning experience. In particular, it facilitates the formation of mobile learning groups, enhancing student/teacher interaction and sharing open educational resources (OERs). A basic chatbot function is also provided. The LeG app has been tested by students and student survey results are presented in the paper, providing insights into the development of mobile learning groups.

In last two years, universities around the world have been using hyflex teaching due to COVID-19. This allows students to attend physical/online lectures in a flexible manner. A hyflex class comprises classroom students as well as online students. In this paper, we present a model for hyflex classrooms that highlights 4Cs: Content, Collaboration, Community and Communication. Based on the 4C model, a hyflex classroom has been designed and implemented through various teaching/learning tools or elements. These include the effective use of presentation slides, annotations, chatbox, open education resources, multiple choice exercises, group exercises etc. The effectiveness of these tools/elements were evaluated by means of an initial student survey. These results provide valuable insights into hyflex teaching/learning.

This paper presents an innovative C3(C-cube) Model-Map for teaching entrepreneurship and shares the experience of using this C3Model-Map in a freshman seminar subject for computing students. Comprising three core elements: Customer, Concept and Company (C3), it can be used to shape a business model (e.g., for technology startups). In other words, students can use a concise and systematic model to frame their business ideas. This seeks to foster both analytical thinking and creative thinking. The teaching methodology and some evaluation results are also presented in this paper.

In this paper, we present an innovative open educational resource (OER) competition for students to suggest and create OERs. The competition is based on a 3E model (Enriching lectures with OERs, Extending classroom learning through OERs, and Elevating student learning with OERs), as well as a flipped learning approach (i.e., students teaching others as teachers). Student learning enhancement is evaluated using nine learning principles/catalysts. Both quantitative and qualitative evaluations are presented and discussed. In particular, the student learning reflections provide valuable insights into how the OER competition can transform student learning (e.g., with reference to the Bloom’s Taxonomy/Model), including their learning attitude. The results indicate that OER competition can provide an effective method to enhance student learning, complementing traditional teaching/learning.

In this paper, we spotlight vehicle-to-everything (V2X) communications in 5G cellular networks. Cellular V2X (C-V2X) communications in 5G enable more advanced services with requirements of ultra-low latency and ultra-high reliability. How to make full use of the limited physical-layer resources is a key determinant to guarantee the quality of service (QoS). Therefore, resource allocation plays an essential role in exchanging information between vehicles, infrastructure, and other devices. In order to intelligently and reasonably allocate resources, a self-adaptive fuzzy logic-based strategy is developed in this paper. To evaluate the network performance for this adaptive strategy, a system model for V2X communications is built for urban areas, and typical safety and non-safety services are deployed in the network. Simulation results reveal that the proposed fuzzy logic-based algorithm can substantially improve resource utilization and satisfy the requirements of V2X services, compared with prior counterparts, which cannot provide guaranteed services due to low resource utilization.

Recent years have seen considerable interest in mobile cloud computing and edge cloud computing. This paper presents a mobile Intercloud system for supporting mobile cloud computing in general and edge cloud computing in particular. In essence, a mobile user with a mobile terminal can set up a virtual mobile terminal with applications and data in a central/home cloud. The virtual mobile terminal can facilitate task and computation offloading and other functions. Moreover, when a mobile terminal joins an edge cloud, the virtual mobile terminal (including required applications and data) can be migrated to enhance system efficiency and the user experience (e.g., shorter access delays). An experimental prototype has been developed for evaluating certain basic object transfer functions. To support the application transfer function, we formulate both finite‐ and infinite‐horizon Markov decision models to determine decision policies (i.e., should an application be transferred to an edge cloud). The transfer decision depends on various factors, including transfer cost, duration associated with the edge cloud, usage probability, and usage cost in the central cloud and edge cloud. Based on the models, we obtain closed‐form solutions for the decision policies, which can be expressed in meaningful formulas to provide useful insights for edge cloud computing in general. To evaluate the mobile Intercloud system for edge cloud computing, we conducted extensive evaluations, including experimental evaluation for testing the basic functions and protocols, analytical evaluation for studying the analytical models, and simulation evaluation for analyzing performance in a multiuser and multicloud environment in particular. The experimental, simulation, and analytical results provide useful insights into the design and development of the mobile Intercloud system for edge cloud computing as well as decision policies for application transfer.

With the advent of the Internet, there is now a vast amount of useful learning resources available. These public resources or Open Educational Resources (OERs) can complement traditional teaching/lectures and student learning. In this paper, we make two contributions to the development of OERs for the global education community. First, we analyze the popular computing/IT-related OERs at MERLOT, one of the major OER repositories in the world. Through the analysis of peer reviews and other data, we present interesting findings and valuable insights for the development of OERs, particularly for the computer science discipline. Second, we present an innovative 3E (Enrich, Extend, Elevate) strategy/pedagogy for the use of OERs with the aim of enhancing student learning from different perspectives. In particular, students can play an important role, to find and even create OERs to enhance their learning to a new dimension.

Smart Learning Environment (SLE) aims at promoting personalized education in various form with different settings fitting the learners' needs. Many works have done to realise the environment for academic studies. However, the development of the generic competencies is another key element of education. The engagement of students in the developmental activities of generic competencies (GDA) is a main concern of the organizers in tertiary education institutions, particularly the student affair offices. They want to have some predictors to reflect the participation of students with some identifiable factors so that the provision can planned correspondingly. In this work, we attempted to the evaluation on a set of attributes of students to their participation on the GDA by means of the correlation and the classification through logical regression. We studied the records of 1649 graduates in a tertiary education institution across two academic years and found that some single factors are reliable in predicting the tendency of students in taking part in the GDA.

The blockchain technology provides a data authentication and permanent storage solution to the data volatility issue in peer-to-peer games. In this work, we present the Infinity Battle, a serverless turn-based strategy game supported by a novel Proof-of-Play consensus model. Comprising three major phases: matchmaking, gaming session and global synchronization, the proposed demo game generates a blockchain through distributed storage and processing.

This paper presents a general framework of an innovative TOUR model with four interrelated elements: Transformation, Outreach, Unification and Reinforcement, enhancing the learning experiences of computer science/computing students via a study tour. We brought our students on an overseas trip as an integral part of an academic course. The immediate goal of the study tour was to gear the students toward the program learning outcomes. Another goal was to take a first step in supporting the TOUR model, to immerse students within these four interrelated important learning and self-improvement elements, and to support each student in becoming a better person. The study tour comprises six core learning activities aligned with the TOUR elements. Evaluations were conducted based on a student survey and self-reflection. The results provide valuable insights into the design of the computer science student study tour, as well as the potential value of the TOUR model.

With the advent of cloud computing and mobile computing, many smart computing applications for mobile data management can be developed. In this paper, we present a development framework and tool for developing innovative mobile Intercloud applications. By means of mobile Intercloud, data can be transferred and processed through the collaboration of clouds as controlled by a mobile terminal. To facilitate the development of mobile Intercloud applications, we have developed a package of App Inventor blocks. Working with the InterCloud Communications Protocol, these graphical programming blocks allow various mobile Intercloud applications to be developed effectively and efficiently. Three innovative applications are presented to illustrate the benefits of mobile Intercloud applications. An evaluation and performance analysis were conducted for an automatic file transfer application. The evaluation and results provide valuable insights into the design of smart computing applications in general and mobile Intercloud applications in particular.

Intercloud seeks to facilitate resource sharing among clouds. To support Intercloud, a trust evaluation framework among clouds and users is required. For trust evaluation, conventional protocols are typically based on a centralized architecture focusing on a one-way relationship. For Intercloud, the environment is highly dynamic and distributed, and relationships can be one-way or two-way (i.e., clouds provide services to each other). This paper presents a distributed trust evaluation protocol with privacy protection for Intercloud. The new contributions and innovative features are summarized below. First, feedback is protected by homomorphic encryption with verifiable secret sharing. Second, to cater to the dynamic nature of Intercloud, trust evaluation can be conducted in a distributed manner and is functional even when some of the parties are offline. Third, to facilitate customized trust evaluation, an innovative mechanism is used to store feedback, such that it can be processed flexibly while protecting feedback privacy. The protocol has been proved based on a formal security model. Simulations have been performed to demonstrate the effectiveness of the protocol. The results show that even when half of the clouds are malicious or offline, by choosing suitable operational parameters the protocol can still support effective trust evaluation with privacy protection.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

For cloud data storage, data privacy and security are two key concerns. Although sensitive data can be encrypted before they are stored in the cloud, the encrypted data can hardly be processed efficiently. Hence, a lightweight solution is required to satisfy both high security and high efficiency requirements. In this paper, we study the problem of range query over encrypted data. The main idea is to transform the range comparison to a privacy-preserving set intersection operation. To protect record privacy, our scheme builds searchable encrypted indexes for records that are secure against inference attack. To ensure the privacy of range queries, non-deterministic encryption, which has not been achieved in range query before, is proposed to hide the search pattern of queries. During range comparison, our scheme neither leaks the order relationship between the upper/lower bound of a range query and the encrypted index, nor produces false positives in the query results. We have implemented our scheme and evaluated its performance in comparison with other schemes. The comparison results indicate that our scheme has a shorter index size and search time than the order-revealing encryption (ORE) scheme when the processing unit is large. Meanwhile, our scheme only leaks the access pattern, and is proved to be more secure than existing schemes.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

In recent years, there has been considerable interest in setting up technology-focused communities of practice for teaching and learning purposes. Instructors and students can play a key role in these communities of learning by creating and/or using Open Educational Resources (OERs). In 2016 two new discipline-specific communities were created within the MERLOT OER user community: Information Systems and Information Technology (IT/IS), and Computer Science (CS). The OER taxonomies for these, predicated on the CSAB/ABET curricula were a key factor in the endorsement of these communities and their portals, by the IEEE Computer Society and the IEEE Education Society. This paper describes the process of creation of both communities with the aim of establishing Editorial Boards to peer review OERs in these disciplines. Moreover, some analytics of the recently-created IT Editorial Board in MERLOT are presented as well.

Searchable encryption seeks to support untrusted third parties to conduct direct searching over encrypted data. However, recent research has found that searchable encryption is vulnerable to attacks, which exploit the statistical relationship or pattern identified from encrypted query results. In this paper, we study the problem of access pattern leakage attack on searchable encryption under a multi-cloud environment. Basically, both database records and queries are distributed among different cloud servers, so that each cloud server can only have partial information about queries and their results. To minimize the query response time while protecting information disclosure, we formulate the record and query assignment as an optimization problem, and solve the problem (i.e., finding the best possible solution) by the minimum s-t cut algorithm. Numerical results show that on average 13% access pattern information can be saved by our assignment strategy while maintaining good query response time.

The introduction of the Bluetooth 4.0 and Bluetooth Low Energy (BLE) standard greatly facilitates the development of Internet of Things (IoT) applications. Most of these applications require a positioning mechanism to detect the position of both people and objects. While BLE is a key enabling technology, it is relatively new as compared to Wi-Fi and RFID. Hence there is a need to conduct more studies on BLE-based positioning methods. In general, positioning methods based on signal propagation and fingerprint are commonly used in wireless networking. These methods have their own limitations in terms of practical use and ease of implementation. In this paper, we present an innovative BLE-based positioning methodology called BluePrint which makes use of a detection mechanism called NUFO (Near, Uncertain, Far and Out). It combines a simple fingerprint-like method with a rule-based algorithm to estimate positions. Experimental results show that Blueprint with NUFO detection can achieve good performance as compared to other methods. Furthermore, its implementation is simple and practical.

In recent years, there has been considerable interest in studying intercloud with the aim of supporting interactions among different clouds, possibly managed by different service providers. The extension of intercloud to a mobile environment, called a "mobile intercloud system" is a relatively new research area. In this paper, we present a mobile intercloud system, which is developed based on the IEEE P2302 Intercloud architecture and inspired by the mobile Internet protocol. Basically a mobile terminal is associated with a home cloud in which a virtual mobile terminal can be set up together with the mobile applications and data. When a mobile terminal moves to a new area and joins a foreign cloud, certain mobile applications and data can be transferred to the foreign cloud. For data/files, we present a rule-based policy so that users can specify the rules for transferring data/files flexibly. A prototype has been developed to demonstrate the basic concept. For applications, we formulate a Markov decision process model to study how the applications should be transferred to minimize the overall cost. Analytical results are presented to provide valuable insights into the design of the mobile intercloud system.

With the growing number of cloud users and the popularity of cloud services, there has been considerable interest in studying Intercloud models and architectures. Inspired by the existing IEEE P2302 Intercloud framework and standards, this paper presents an Intercloud architecture for Intercloud communications, focusing on resource discovery. An Intercloud system seeks to facilitate the sharing of resources among different clouds so that cloud resources can be used more efficiently and effectively. In general, resources sharing involves three main steps: discovering resources, selecting resources and allocating resources. This paper seeks to study a DNS-based method for discovering cloud resources. Based on an Intercloud architecture, we also develop analytical models by using queuing theory, and examine the impact of different parameters on the performance of the resource discovery process. The performance of two models, sequential search and broadcast search, are compared and analyzed. The main objectives of the modeling are to evaluate the performance and investigate the constraints of these two models, and determine a better resources discovery method that minimizes the average response time.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Cloud service selection and financial expense are two main concerns of users considering adoption of cloud computing services. In this paper, we propose a novel cloud federation that is cognitive to the dynamic prices. The cloud federation system first determines on which cloud services should the user applications be deployed. Then, when a cloud provider is charging too high for a VM, the proposed system automatically migrates user tasks to a cloud system that is charging at a lower rate. We discuss the architectural framework and platform design, provide a mathematic formulation and investigate a total service fee minimization approach with privacy constraints. Preliminary simulation results demonstrate the proposed system can lower the cost of cloud services by exploiting the advantages of different price policies provided by multiple cloud providers.

Contrary to conventional gaming-on-demand services that stream gaming video from cloud to players' terminals, a decomposed cloud gaming platform supports flexible migrations of gaming components between the cloud server and the players' terminals. In this paper, we present the design and implementation of the proposed decomposed gaming system. The cognitive resource optimization of the system under distinct targets, including the minimization of cloud, network, and terminal resources and response delay, subject to quality of service (QoS) assurance, is formulated as a graph partitioning problem that is solved by exhaustive searches. Simulations and experimental results demonstrate the feasibility of cognitive resource management in a cloud gaming system to efficiently adapt to variations in the service environments, such as increasing the number of supported devices and reducing the network bandwidth consumption of user terminals, while satisfying different QoS requirements for gaming sessions. We also suggest two heuristic algorithms based on local greedy and genetic algorithm approaches, which can potentially provide scalable but suboptimal solutions in large-scale implementations.

Cloud gaming systems host the game in the cloud, while Gameplays and views are streamed to the players' terminals in the form of encoded video frames. To address the high-bandwidth issue of real-time gaming video transmission, we have proposed a cloudlet-assisted multiplayer cloud gaming system to encourage cooperative video sharing, which exploits the similarities of video frames among multiple players in the same crowd playing the same game via a secondary ad hoc network. In this paper, we provide a detailed modeling of the proposed system, including the correlation between video frames, mobility of terminal devices, and diversity of network quality of service for distinct players. With necessary mathematical formulations, we study the players' behaviors regarding the cooperative sharing patterns to optimize the system performance in terms of the quality of users' experience. Also, heuristic algorithms are proposed to reduce the computational complexity. Empirical study and trace-driven simulation results illustrate the impact of mobility on the system performance and show that the proposed solution is able to provide better quality of experience compared with the existing platform.

In contrary to conventional gaming-on-demand solution, cognitive cloud gaming platform facilitates gaming component migration from the cloud server to the players' terminal, a novel flexible solution to provide Gaming as a Service. In this work, we model the component-based game and investigate the capacity of intelligent resource management for different optimization targets, including cloud resource minimization and throughput-oriented optimization. Experimental results show that, with the cognitive resource management, cloud system is adaptive to various service requirements, such as increasing the quantity of supported devices and reducing the network throughput of user terminals, while satisfying players' quality of experience.

An important category of mobile RFID systems is the RFID system with mobile RFID tags. The mobility of RFID tags poses new challenges to designing RFID anti-collision protocols. Existing RFID anti-collision protocols cannot support high tag moving speed and high identification rate simultaneously. These protocols do not distinguish the identification deadlines of moving tags. Also, when tags move fast, they cannot determine the number of unidentified tags in the interrogation area of an RFID reader. In this paper, we propose a schedule-based RFID anti-collision protocol which, given a high identification rate, achieves the maximal tag moving speed. The protocol, without the need to estimate the number of unidentified tags, schedules an optimal number of tags to compete for the channel according to their identification deadlines, so as to achieve the optimal identification performance. The simulation and experiment results show that our approach can increase the moving speed of tags significantly compared with existing approaches, while achieving a high identification rate.

The increasing density of NAND flash memory leads to a dramatic increase in the bit error rate of flash, which greatly reduces the ability of error correcting codes (ECC) to handle multibit errors. NAND flash memory is normally used to store the file system metadata and page mapping information. Thus, a broken physical page containing metadata may cause an unintended and severe change in functionality of the entire flash. This paper presents Meta-Cure, a novel hardware and file system interface that transparently protects metadata in the presence of multibit faults. Meta-Cure exploits built-in ECC and replication in order to protect pages containing critical data, such as file system metadata. Redundant pairs are formed at run time and distributed to different physical pages to protect against failures. Meta-Cure requires no changes to the file system, on-chip hierarchy, or hardware implementation of flash memory chip. We evaluate Meta-Cure under a real-embedded platform using a variety of I/O traces. The evaluation platform adopts dual ARM Cortex A9 processor cores with 64 Gb NAND flash memory. We have evaluated the effectiveness of Meta-Cure on the new technology file system file system. Experimental results show that the proposed technique can reduce uncorrectable page errors by 70.38% with less than 7.86% time overhead in comparison with conventional error correction techniques.

Inter-core communication introduces overheads in task schedules on Multiprocessor System-on-Chips (MPSoCs). Inter-core communication overhead not only negatively impacts the timing performance but also significantly degrades the memory usage for streaming applications running on MPSoC architectures. By minimizing inter-core communication overhead, a shorter period can be applied and system performance (e.g., throughput, memory usage) can be improved. In this paper, we focus on solving the problem of minimizing inter-core communication overhead for streaming applications on bus-based MPSoCs. The objective is to minimize inter-core communication overhead while minimizing the overall memory usage. To solve the problem, we first let tasks with intra-period data dependencies transform to inter-period data dependencies so as to overlap the execution of computation and inter-core communication tasks. By doing this, inter-core communication overhead can be effectively removed. To minimize the overall memory usage, we then perform schedulability analysis and obtain the bounds of the times needed to reschedule each task. Based on the schedulability analysis, we formulate the scheduling problem as an integer linear programming (ILP) model and obtain an optimal schedule. In addition, we propose a heuristic approach to efficiently obtain a near-optimal solution. We conduct experiments on a set of benchmarks from both real-life streaming applications and synthetic task graphs. The experimental results show that the proposed approach can significantly reduce the schedule length and improve the memory usage compared with the previous work.

The linear scaling down of NAND flash memory is approaching its physical, electrical, and reliability limitations. To maintain the current trend of increasing bit density and reducing bit per cost, 3-D flash memory is emerging as a viable solution to fulfill the ever-increasing demands of storage capacity. In 3-D NAND flash memory, multiple layers are stacked to provide ultrahigh density storage devices. However, the physical architecture of 3-D flash memory leads to a higher probability of disturbance to adjacent physical pages and greatly increases bit error rates. This paper presents a novel physical-location-aware address mapping strategy for 3-D NAND flash memory. It permutes the physical mapping of pages and maximizes the distance between the consecutively logical pages, which can significantly reduce the disturbance to adjacent physical pages and effectively enhance the reliability. The proposed mapping strategy is applied to a representative flash storage system. Experimental results show that the proposed scheme can reduce uncorrectable page errors by 70.16% with less than 10.01% space overhead in comparison with the baseline scheme.

It is challenging to design effective scheduling algorithms for multimedia transmissions over wireless channels that employ adaptive modulation and coding (AMC). On the one hand, it is desirable for the overall system throughput to be enhanced by taking advantage of multi-user diversity. On the other hand, fairness or QoS guarantees need to be maintained for individual users, especially in the case of multimedia applications that have strict delay requirements. In this paper, we propose a novel scheduling algorithm called QoS-based cross-layer scheduling (QoS-CLS) to achieve a good design tradeoff. To maximize the system throughput, the algorithm takes into account the information on both the physical layer and the data link layer to schedule user transmissions. Using cross-layer information, the scheduling problem is formulated as a Markov Decision Process and the optimal decision policy (based on the channel status, traffic state, and buffer status of each traffic flow) is pre-calculated by linear programming. This policy is then stored in the system for scheduling in real-time. Simulation results show that QoS-CLS can greatly enhance the channel throughput compared to existing algorithms because of its cross-layer QoS consideration and the optimization method. Moreover, it can provide QoS guarantees while achieving efficient resource sharing among different traffic flows.

Most previous work on code division multiple access (CDMA) considers the bit error ratio (BER) at the physical layer and the frame drop ratio (FDR) at the medium access control layer separately. However, a better system performance, e.g., in terms of a lower overall frame loss ratio (FLR), can be achieved if BER and FDR are jointly optimized. In this paper, we propose a cross-layer optimization scheme called traffic-adaptive scheme for multicode CDMA operating over a time division multiple access (TDMA) channel. Based on the traffic condition and buffer status, this scheme employs a Markov Decision Process (MDP) to determine the optimal value of the maximum number of simultaneous data frames that can be transmitted in each time slot of a TDMA frame so as to minimize the overall FLR of the system. To facilitate implementation, we also propose an approximation scheme named the rate-adaptive scheme to reduce the computation cost. Simulation and analytical results show that both the traffic-adaptive scheme and rate-adaptive scheme can significantly reduce FLR, increase the system throughput, and optimize the packet access delay of the system. Furthermore, the rate-adaptive scheme can achieve a performance close to the traffic-adaptive scheme when the traffic load in the system is high.

Abstract Mobility management, which includes location management and handoff management, is essential in cellular wireless networks to provide service to mobile users. Location management enables call delivery to mobile users, while handoff management maintains the connectivity of ongoing calls while users move between cells. In next generation networks, mobile users will avail themselves with terminals capable of accessing wireless networks employing multiple technologies, thus making the task of mobility management more challenging. This paper reviews recent developments in location management, and surveys methods for handoff management between heterogeneous systems. Methods for inter‐system handoffs in packet‐switched inter‐networks are discussed according to the protocol layer in which the handoffs take place, i.e., network layer, transport layer, and application layer. Open problems for mobility management in future wireless networks are also presented. Copyright © 2010 John Wiley & Sons, Ltd.

Communication systems are becoming more complicated to support different types of services. How to coordinate different services around a user in a flexible and customized way is a new and interesting challenge. Service providers have proposed solutions such as the Universal Communication Identifier

Efficient communications are crucial for disaster response and recovery. However, most current public safety land mobile radio (LMR) networks only provide narrowband voice service with limited support of low-speed data services. In this paper, we study to enhance the interoperability of LMR with commercial wireless cellular networks, by which a wide variety of benefits can be offered to disaster responders, including new multimedia services, increased data rates and low cost devices. Our approach is based on Session Initiation Protocol (SIP) and a joint radio resource management framework. We use a novel SIP- based seamless handoff scheme to support the interoperability between cellular and LMR networks. In addition, an optimal radio resource management scheme is proposed to maximize the overall radio resource utilization and at the same time guarantee service availability and continuity quality of service (QoS) for disaster responders. The effectiveness of the proposed schemes is illustrated by numerical examples.

It is a big challenge to design an effective scheduling algorithm for multimedia transmissions over a wireless channel that employs adaptive modulation and coding (AMC). On one hand, the scheduling algorithm needs to schedule user transmissions by taking advantages of the channel diversity so that the overall system performance can be improved. On the other hand, the algorithm also needs to maintain fairness among users and to provide QoS guarantee based on user requirements. In this paper, we propose a novel scheduling algorithm called QoS-based cross-layer scheduling algorithm (QoS-CLS) to address the aforementioned issues. To maximize the system throughput, the algorithm takes into consideration both the physical layer and data link layer information to schedule user transmissions. Using the cross-layer information, the scheduling problem is formulated into a Markov Decision Process (MDP) and the optimum decision policy (based on the channel status, traffic state and buffer status of each traffic flow) is pre-calculated by linear programming and stored in the system for scheduling in real-time. Results show that QoS-CLS can greatly enhance the channel throughput compared to the opportunistic scheduling algorithm because of its cross-layer QoS consideration and the optimization method. Moreover, it can provide QoS guarantee and facilitate resource sharing among different traffic flows.

In this paper we first give an overview of an isochronous coordination function (ICF) for supporting voice services over IEEE 802.11 wireless local area networks (WLANs). By emulating a dynamic TDMA-like service, ICF can reduce polling overhead while minimizing consecutive packet losses. Next we present a Markov model to analyze the average reconnection failure ratio, average packet loss ratio, and average good put of the ICF method under three different reconnection schemes. In particular close form solutions are obtained. The model can also be extended to analyze other polling-based protocols. Therefore it provides a valuable insight into the design of polling-based protocols for supporting isochronous voice traffic over WLANs.

Previous work on code division multiple access (CDMA) often considers the bit error ratio (BER) at the physical layer and the frame drop ratio (FDR) at the medium access control (MAC) layer separately. However, better system performance (e.g., lower overall packet loss ratio (PLR)) can be achieved if BER and FDR are jointly optimized. This paper, the authors first set up a Markov chain model to evaluate the performance of transporting multimedia traffic over a multi-code CDMA network. Then, the authors propose two novel cross-layer optimization methods that dynamically adjust the maximum number of simultaneous transmissions according to the traffic arrival rate and the queue status, respectively. Simulation and analytical results show that these two methods can significantly reduce PLR and increase the system throughput.

One of the prominent goals of next-generation mobile communication systems is to support seamless roaming of users across heterogeneous wireless access networks. Although SIP has been regarded as an attractive candidate to provide mobility management in B3G/4G networks because of its flexibility and ease of deployment, it still suffers from unacceptably long handoff delays. In this paper, a SIP-based seamless-handoff (S-SIP) scheme is proposed to overcome this problem in inter-domain roaming. Unlike the other SIP-based handoff methods, S-SIP employs a "make-before-break" procedure for seamless handoffs. Moreover, we also propose the appropriate handoff triggering point for this scheme based on location tracking techniques. Simulations results show that the proposed scheme greatly outperform the general SIP-based handoff scheme.

We present MAGICS, a mobile agent-based system for supporting business-to-consumer electronic commerce (e-commerce) or mobile commerce (m-commerce) applications. To use the system, consumers first provide their buying requirements to a proxy/agent server through a Web browser or a wireless application protocol (WAP) terminal. Having obtained the requirements, mobile agents are generated to carry out tasks for the consumers including getting offers from merchants, evaluating offers, and even completing purchases. In the case of mobile commerce, consumers can generate a mobile agent to conduct a search and evaluation in the digital marketspace before making a purchase in the physical marketplace. To make it possible to choose an offer that best satisfies the consumer's requirement(s), we present a mathematical model for evaluating multiple decision factors. To test the basic functions of the mobile agent-based Internet commerce system (MAGICS), we have built a prototype system. To minimize the average cost of a product (including the cost of sending agents), we have also developed an analytical model that can determine how many agents should be sent to compare prices. Four different price distributions and some real price information are analyzed based on the model. The analysis provides valuable insights into the design of mobile agent-based shopping applications for m-commerce, in particular, and for e-commerce, in general.

Recent advances in signal processing techniques have enabled wireless networks to have multi-packet reception (MPR) capability at the physical layer, where it is possible to receive more than one packets when concurrent transmissions occur. In this paper, we propose a novel multi-reservation multiple access (MRMA) scheme for future wireless multimedia networks based on such an MPR channel model. MRMA can fully exploit the channel's MPR capacity while fulfilling the quality of service requirements of different multimedia traffic. Similar to many existing reservation protocols, MRMA guarantees (i) bounded access delay for real-time traffic by dropping packets not transmitted within the required delay bound, and (ii) satisfaction of the required packet loss ratio when applied in conjunction with a connection admission control method to limit the number of admitted traffic streams. MRMA further incorporates a priority control mechanism to differentiate guaranteed and best-effort services for real-time voice/video and connectionless data, respectively. Analytical and simulation results are presented to illustrate the effectiveness of MRMA in service differentiation and increasing the number of admitted traffic streams

Next-generation mobile communication systems will provide "always best connected" services to mobile users via cellular networks that provide wide area coverage for global access, complemented by broadband wireless networks (BWNs) at hotspots to accommodate higher traffic intensities. In such a heterogeneous network, a user entering a hotspot has the option to handoff to the BWN for better services. However, each vertical handoff also causes some momentary service degradations. Since the enhancement of user satisfaction by a vertical handoff depends on the user's sojourn time in the BWN, the handoff decision should consider the user's location and mobility, in order to optimize the user's satisfaction. In this paper, we propose a novel vertical handoff decision algorithm based on dynamic programming, utilizing the location information of mobile users. Simulation results show the effectiveness of the algorithm compared with other recently proposed schemes.

This paper presents an auction system based on mobile agents. By using a proxy server, a user can generate a mobile auction agent by giving the bidding information, including the maximum bidding price. The agent then moves to the required server to participate in the auction according to the user's requirements. A major contribution of the paper is that it presents a mathematical model to analyze the commonly used "proxy bidding method." Based on the distribution of the maximum bidding price, the model can be used to find the probability of stopping at a certain price and, hence, the average winning price. Simulation and analytical results are presented to demonstrate the behavior of the system.

We present an active MPLS service with bandwidth reservation for an advanced network called ISDN3. In essence, an active packet is employed to reserve a particular amount of bandwidth of a label switched path according to an adaptive pricing method. To maximize the network provider's earnings, a bandwidth selling policy is determined based on a Markov decision model. Analytical and simulation results are presented comparing the proposed bandwidth selling policy with two other schemes.

.Ahlract-Mohile IP is one of the dominating protocols that provide the mohilily support in the Internet. However, even with some proposed optimizntion techniques, there is still space far improving the performance, In this paper, IYC present a novel mnilhns-hnsed scheme to further improve the performance. In this scheme. each mobile node miq-nting to a foreign network is associated with U mailbor. A sender sends packets to the receiver's mailbox, which will in turn foianrd them to the destination. During handuff, a mobile node can decide whether to move its mailbox and rcpnrl the handoff to the home agent, or simply to report the hnndaff to the mailbor. In this way. the scheme is adaptke and can hc made to reduce the workload on the home agent and minimize the total cost of message delivery and mohilily management. To evaluate the performance of the propnsrd schrmr, we develop a performance model considering two walk models for mobile nodes. based on which the cost function is derived We also propnse an iterative algorithm for deriving an optimal point where the cost function reaches its minimum. The results show that our new scheme c m outperform Mobile 1P route optimization with smooth handoff extension, no matter how mnny packets are to he received during each migration.

In this paper, we propose a dynamic reservation protocol for the low earth orbit (LEO) mobile satellite system. Based on an analytical model, the dynamic reservation protocol enhances system performance by dynamically varying both the access probability and reservation bandwidth. To implement the protocol, a novel contention-pattern-analysis method is proposed to estimate the number of contending terminals at the start of a frame. The reservation protocol is employed to integrate connection-oriented and connectionless traffic over a satellite channel. Simulation and theoretical results are presented to analyze the performance of the protocol and illustrate its benefits.

Two of the fundamental issues in designing protocols for message passing between mobile agents (MAs) are tracking the migration of the target agent and forwarding messages to it. Even with an ideal fault-free network-transport mechanism, messages can be dropped during MA migration. Therefore, in order to provide reliable message delivery, protocols need to overcome message loss caused by asynchronous operations of agent migration and message forwarding. In this paper, two known message forwarding approaches, namely push and pull, are explored to design adaptive and reliable message delivery protocols. Based on a commonly used MA tracking model, the pros and cons of these two approaches are evaluated, both qualitatively and quantitatively. The comparative performance evaluation is presented in terms of network traffic and delay in message processing. We also propose improvements to the pull approach to reduce network traffic and the message delay. We conclude that with different message passing and migration patterns and varying requirements of real-time message processing, specific applications can select different message delivery approaches to achieve the desired level of performance and flexibility.

This paper presents an automatic secretary system called ASSIST (Automatic Secretary System using Internet and Smart-agent Technologies), which provides basic secretarial services, particularly meeting scheduling. We formulate a meeting scheduling problem based on a Markov decision model. The backward induction algorithm is used to determine the optimal policy (i.e., the optimal number of time slots for scheduling purposes). The analytical results are presented to show the system's behavior.

To enable secure Internet protocol (IP) multicasting, a scaleable and effective re-keying mechanism is required to safeguard the multicasted information. This paper presents a hybrid re-keying mechanism that combines the advantages of the centralized and distributed re-keying methods. Simulation results are presented to evaluate the performance in comparison with other re-keying methods.

We present a bidding strategy that enables an agent to bid in multiple English auctions. Based on a backward induction method, backward induction strategy (BIDS) seeks to maximize the value of a utility function. In general, the agent needs to determine whether to bid in the next available auction. Note that it may be better to stop bidding if the current utility (the utility associated with the current bid price) is less than the expected utility of all of the subsequent auctions. Simulation results demonstrate the advantages of BIDS over other strategies.

A new routing method, known as active routing, has been emerging. This involves using active packets to configure customized network paths. Based on a Markov decision model, this paper presents an active routing service for active networks in general and the next generation network, called ISDN3, in particular. Our aim is to determine the active routing policy so as to minimize the network cost. Theoretical analysis is presented to show the advantages of our proposal as compared with three other approaches.

Two of the fundamental issues in message passing between mobile agents are tracking the migration of the target agent and delivering messages to it. In order to provide reliable message delivery, protocols are needed to overcome message loss caused by asynchronous operations of agent migration and message forwarding. In this paper, two message forwarding approaches, namely push and pull, are explored to design adaptive and reliable message delivery protocols. The pros and cons of these two approaches are evaluated, both qualitatively and quantitatively. The comparative performance evaluation is in terms of network traffic and delay in message processing. We also propose improvements to the pull approach to reduce network traffic and the message delay. We conclude that with different communication and migration patterns and requirements of real-time message processing, specific applications can select different message delivery approaches to achieve the desired level of performance and flexibility.

A dynamic reservation time division multiple access (DR-TDMA) control protocol that extends the capabilities of asynchronous transfer mode (ATM) networks over the wireless channel is proposed in this paper. DR-TDMA combines the advantages of distributed access and centralized control for transporting constant bit rate (CBR), variable bit rate (VBR), and available bit rate (ABR) traffic efficiently over a wireless channel. The contention slots access for reservation requests is governed by the framed pseudo-Bayesian priority (FPBP) Aloha protocol that provides different access priorities to the control packets in order to improve the quality-of-service (QoS) offered to time sensitive connections. DR-TDMA also features a novel integrated resource allocation algorithm that efficiently schedules terminals' reserved access to the wireless ATM channel by considering their requested bandwidth and QoS. Integration of CBR, voice, VBR, data, and control traffic over the wireless ATM channel using the proposed DR-TDMA protocol is considered in this paper. Simulation results are presented to show that the protocol respects the required QoS of each traffic category while providing a highly efficient utilization of approximately 96% for the wireless ATM channel.

In this paper, we extend our previous dynamic reservation integrated services multiple access (DRISMA) protocol for the integration of constant bit rate (CBR), variable bit rate (VBR) and unspecified bit rate (UBR) traffic over wireless ATM networks. DRISMA provides CBR services by pre-assigning slots in a frame and VBR services by reserving slots on a bandwidth-on-demand basis. By using a request-mini-slot method, it also ensures that UBR traffic only utilizes the residual bandwidth of the CBR and VBR traffic. However, our previous DRISMA protocol provides isochronous services only. In this paper, we propose a novel credit-based scheme for supporting bursty VBR traffic more effectively. This paper describes the operation of the credit-based scheme and presents some simulation results to illustrate its performance.

This paper proposes data and voice scheduling algorithms for the dynamic reservation time division multiple access (DR-TDMA) MAC protocol for wireless ATM networks. Featuring a novel framed pseudo-Bayesian priority ALOHA algorithm that provides access priority to voice control packets, DR-TDMA improves the quality-of-service offered to voice connections and increases the maximum throughput for integrated voice and data traffic. The DR-TDMA protocol can also be extended to integrate constant bit rate (CBR) and variable bit rate (VBR) traffic in general. Simulation results show that the DR-TDMA protocol can achieve throughput in the range of 96% while maintaining reasonable quality of service for data traffic and a voice loss rate lower than 1%.

Path optimization is required for those connection rerouting schemes where the path after an inter-switch handoff is not optimal. In this paper, we evaluate the performance of three path optimization schemes (namely: exponential, periodic, and Bernoulli) for the two-phase inter-switch handoff protocol. Using analytical modeling and simulation, we determine the optimal operating point and the minimum expected cost for each scheme. We also study the effect of the relative change of the expected cost when the estimates of the average call duration or the mean time between inter-switch handoff are inaccurate. Results indicate that the Bernoulli scheme provides the lowest expected cost per call, while the periodic scheme is relatively insensitive to the changes of the average call duration.

The explosive growth of Internet users, the increased user demand for bandwidth, and the declining cost of technology have all resulted in the emergence of new classes of high-speed distributed IP-router architectures with packet-forwarding rates of the order of gigabits, or even terabits, per second. This paper develops an analytical framework for modeling and analyzing the impact of technological factors on the cost-performance tradeoffs in distributed-router architectures. The main tradeoff in a distributed router results naturally from moving the main packet-forwarding and processing power from a centralized forwarding engine to an ensemble of smaller forwarding engines, either dedicated to or shared among the line cards. Processing packets in these smaller engines can be much cheaper (by as much two to three orders of magnitude) than in a centralized forwarding engine. Therefore, the main goal of our modeling framework is to determine an optimal allocation of processing power to the forwarding engines (in a distributed router) to minimize overall router cost while achieving a given level of packet-forwarding performance. Two types of router models are analyzed using the proposed framework: a distributed-router architecture and parallel-router architecture.

Metropolitan area networks (MANs) are well suited to serve as broadband multiplexers for asynchronous transfer mode (ATM) networks, to facilitate enterprise networking and to support future wireless personal communication systems. We propose and analyze a novel reservation arbitrated (RA) access method which provides isochronous voice transport over dual-bus MANs while enabling statistical multiplexing among voice calls. In combination with a new cyclic capturing (CC) mechanism, RA access allows stations to capture and reserve isochronous voice channels in a fair and distributive manner. This paper presents the RA access protocol, derives an analytical model for general waste-free voice reservation protocols, and analyzes the performance of RA access by computer simulations validated by analytical calculations. To assess the actual voice quality, simulation results based on a real voice signal are also presented. Results indicate that RA access offers significant improvements in channel utilization, as compared to prearbitrated (PA) access, while providing an acceptable quality of service. Therefore, RA access offers an efficient voice transport mechanism for existing switched multimegabit data service (SMDS) networks employing the IEEE 802.6 protocol, as well as emerging ATM/MAN-based broadband networks.

One of the major design issues in wireless Am is the support of inter-switch handoffs.An inter-switch handoff occurs when a mobile terminal moves to a new base station connecting to a different switch.Recently a two-phase handoff protocol has been proposed to address this issue.It employs path extension to process the handoff request immediately, followed by possible path optimization to reduce the path cost.To implement the two-phase handoff protocol efficiently, we need to determine when to trigger path optimization.~s paper presents three path optimization schemes, namely: mponential, periodic, and Bernoulli, for the twm phase handoff protocol.A discrete time analytical model is proposed to enable evaluations and comparisons of the expected connection coss between these schemes.A major result is the closed form expression of the expected cost and its minimization at the optimal operating point for each scheme, derived from the andyticd model.Numerical resul~indicate that the performance of all three schemes are comparable, with the Bernoulli scheme outperforming the other two schemes.-F~-.

Metropolitan area networks (MANs) are well suited to support integrated voice and data personal communication services (PCS) by interconnecting wireless base stations (BSs). Whereas data transport is best supported by queue-arbitrated (QA) access to the IEEE 802.6 MAN, several alternatives exist for voice transport, including pre-arbitrated (PA) access, bi-state PA access, QA access, and reservation-arbitrated (RA) access. The voice traffic capacity of these alternatives are compared under different data traffic load. The results indicate that RA access, QA access, and bi-state PA access are preferred under low, medium, and high data traffic load, respectively, as they facilitate statistical multiplexing to almost double the capacity of PA access.