With the development of blockchain technology, an increasing number of devices are joining the network and generating numerous transactions, which pose significant performance and scalability challenges to blockchain networks. Sharding technology is one solution that improves throughput by parallelising transaction validation and block generation, thereby alleviating this challenge. However, during the process of dividing shard groups in large-scale networks, the uneven distribution of malicious nodes or dynamic changes in joined nodes may lead to failures in the availability and liveness of shard groups. This paper proposes an enhanced sharding blockchain system that improves fault tolerance and reliability to ensure high shard group performance, scalability, and reliability. We also propose the concept of a backup pool and achieve the detection and recovery of faulty shards through pre-deployed backup pool nodes and redesigned consensus algorithms. After a thorough security analysis, we conclude that the proposed sharding blockchain system can increase the Resilience of shard groups from 33.3% to 66.6%. Additionally, we evaluate the proposed system, and the results show that it ensures the security, reliability, and high performance of sharding while increasing the scalability of the system’s network nodes from 10 4 to 10 6 compared to existing sharding blockchains.

Split learning (SL) aims to protect user data privacy by distributing deep models between the client-server and keeping private data locally. In SL training with multiple clients, the local model weights are shared among the clients for the local model updates. This paper first reveals data privacy leakage exacerbated by local weight sharing among the clients in SL through model inversion attacks. Then, to reduce the data privacy leakage issue, we propose and analyze privacy-enhanced SL (P-SL) (or SL without local weight sharing). We further propose a parallelized P-SL to expedite the training process by duplicating multiple server-side model instances without compromising accuracy. Finally, we explore P-SL with late participating clients and devise a server-side cache-based training method to address the forgetting phenomenon in SL when late clients join. The experiment results demonstrate that P-SL helps reduce up to$50\%$of client-side data leakage, which essentially achieves a better privacy-accuracy trade-off than the current trend by using differential privacy mechanisms. Moreover, P-SL and its cache-based version achieve comparable accuracy to baseline SL under various data distributions, while incurring lower costs for computation and communication. Additionally, caching-based training in P-SL mitigates the negative effect of forgetting, stabilizes learning, and enables practical and low-complexity training in a dynamic environment with late-arriving clients.

Permissionless blockchain technology offers numerous potential benefits for decentralised applications, such as security, transparency, and openness. BFT-based consensus mechanisms are widely adopted in the permissioned blockchain to meet the high scalability requirements of the network. Sybil attacks are one of the most potential threats when applying BFT-based consensus mechanisms in permissionless blockchain due to the lack of effective verification mechanisms for participants' identities. This paper presents a novel endorsement-based bootstrapping protocol with a signature algorithm that offers a streamlined, scalable identity endorsement and verification process. This approach effectively safeguards the BFT-based consensus mechanism against Sybil attacks. Using our proposed method, we have conducted thorough security analyses and simulation experiments to assess security, robustness, and scalability advantages in large-scale networks. Our results demonstrate that the scheme can effectively address the identity verification challenges when applying BFT-based consensus in a permissionless blockchain.

This paper explores hybrid auction mechanism to incentivize peer-to-peer (P2P) energy trading in decentralized smart grid system to maximize societal welfare. P2P energy trading is a promising approach for leveraging renewable energy sources, allowing users to generate and exchange energy within local networks. In this context, buyers represent consumers, while sellers are prosumers, acting as both energy producers and consumers over time. Buyers are incentivized to procure energy from sellers due to the lower cost and greener source of energy compared to the centralized grid. In addition, the production and dissemination of renewable energy on a smaller scale mitigates the burden on transmission infrastructure, thereby decreasing reliance on the primary power grid. To optimize energy trading, We propose a hybrid auction that takes into account the constraints of grid infrastructure, such as transmission line capacity and related expenses, in order to increase the profitability of energy trading. The mechanism ensures individual rationality, truthfulness, computational efficiency, and fairness in the bidding process. Through mathematical examination and simulation experiments, the hybrid auction mechanism is assessed for its efficacy in enhancing energy trading efficiency and facilitating equitable resource allocation. This research contributes to the advancement of P2P energy trading mechanisms, enabling efficient use of renewable energy resources in decentralized smart grid environment.

Split learning (SL) enables data privacy preservation by allowing clients to collaboratively train a deep learning model with the server without sharing raw data. However, SL still has limitations such as potential data privacy leakage and high computation for clients. In this paper, we propose to binarize the SL local layers for faster computation (up to 17.5 times less forward-propagation time in both training and inference phases on mobile devices) and reduced memory usage (up to 32 times less memory and bandwidth requirements). More importantly, the binarized SL (B-SL) model can reduce privacy leakage from SL smashed data with merely a small degradation in model accuracy. To further enhance privacy preservation, we also propose two novel approaches: 1) training with additional local leak loss and 2) applying differential privacy, which could be integrated separately or concurrently into the B-SL model. Experimental results with different datasets have affirmed the benefits of the B-SL models compared with several benchmark models. The effectiveness of B-SL models against feature-space hijacking attack (FSHA) is also illustrated. Our results have demonstrated B-SL models are promising for lightweight IoT/mobile applications with high privacy-preservation requirements such as mobile healthcare applications.

In An era where technology advances at an unprecedented pace, the healthcare sector stands at the cusp of a transformative revolution. The confluence of distributed Big Data intelligence with instantaneous e-healthcare services heralds a new paradigm, where the boundaries between medicine, artificial intelligence, and data science are blurred, giving rise to innovative solutions that redefine patient care. The emergence of personalized medicine, bolstered by the power of machine learning, graph-based techniques, and real-time analysis, is not merely a technological triumph but a testament to human ingenuity. It's a response to a world grappling with complex diseases, burgeoning healthcare costs, and an ever-increasing demand for precision and efficiency.

Blockchain technology provides a secure and reliable platform for managing data in various application areas, such as supply chain management, multimedia, financial sector, food sector,Internet of Things (IoT), healthcare, and many more. The recent emergence of blockchain with IoT provides significant growth in the healthcare industry to improve security, privacy, efficiency, and transparency with more business opportunities. Nevertheless, conventional healthcare schemes suffer from various security attacks like collusion, phishing, masquerade, etc. Therefore, a privacy-preservingDistributed Application (DA)is proposed in this paper using blockchain technology to create and maintain healthcare certificates. Here, the distributed application provides an interface between the blockchain network and system objects like healthcare centers, verifiers, and regular authorities to generate and issue medical documents. In addition, it also ensures security by specifying rules using various smart contracts. To evaluate the performance of the proposed scheme, various experimental tests are conducted using the Etherscan tool for measuring operation cost, latency, and processing time. Here, the efficiency of the proposed system is also compared to the existing systems in terms of latency, throughput, and response time. The experimental results and comparative analysis show that the proposed work is more efficient than the existing techniques.

Abstract The advancements of the Internet of Things (IoT) and voice-based multimedia applications have resulted in the generation of big data consisting of patterns, trends and associations capturing and representing many features of human behaviour. The latent representations of many aspects and the basis of human behaviour is naturally embedded within the expression of emotions found in human speech. This signifies the importance of mining audio data collected from human conversations for extracting human emotion. Ability to capture and represent human emotions will be an important feature in next-generation artificial intelligence, with the expectation of closer interaction with humans. Although the textual representations of human conversations have shown promising results for the extraction of emotions, the acoustic feature-based emotion detection from audio still lags behind in terms of accuracy. This paper proposes a novel approach for feature extraction consisting of Bag-of-Audio-Words (BoAW) based feature embeddings for conversational audio data. A Recurrent Neural Network (RNN) based state-of-the-art emotion detection model is proposed that captures the conversation-context and individual party states when making real-time categorical emotion predictions. The performance of the proposed approach and the model is evaluated using two benchmark datasets along with an empirical evaluation on real-time prediction capability. The proposed approach reported 60.87% weighted accuracy and 60.97% unweighted accuracy for six basic emotions for IEMOCAP dataset, significantly outperforming current state-of-the-art models.

The advent of 5G and beyond networks paves the way for significant innovations in industrial applications and services. It does not only offer broadband services through mobile networks. Indeed it unleashes application layer innovation. Potentially beneficial to millions of users. Though it looks attractive, it possesses very complex network functions proven to be well defined and consistent. This special issue is hosted to address three major drawbacks in 6G-enabled NIB industrial applications. The first is to implement a portable solution that constitutes a core network product that can be easily implemented across small hardware platforms. The second is to find cost-effective solutions, with each core supporting a small network. Finally, finding new innovative paradigms for 6G enabled NIB that can operate in very challenging environments in a qualitative, flexible, and scalable manner.

Mobile Cloud Computing (MCC) is a developing technology that assists in improving the quality of the mobile services. Since the increase in mobile resources, the researchers have taken the initiative to take into contemplation resource sharing among heterogeneous mobile devices. Therefore, to design a system architecture for mobility models and resource sharing are key issues that require utmost efforts to be solved to achieve anticipated objectives. Therefore, keeping in view the desired goals, in this paper, we present a system architecture based on the hierarchical resource sharing mechanism for MCC. The proposed system architecture is divided into three domains, such as Global Cloud Server (GCS), Local ISP Server (LIS), and Gateway Server (GWS). Also, the novel paradigm for minimizing the delay in the network based on deploying Foglets at each proposed algorithm of clustering mechanism is also present. Moreover, the fuzzy rule-based scheme is proposed to eliminate the inappropriate foglets before deciding an optimal foglet for handover. A foglet selection scheme is developed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision mechanism. Various parameters such as delay, jitter, Bit Error Rate (BER), packet loss, communication cost, response time, and network load are considered for selecting an optimal network. To check the feasibility and performance of the proposed system architecture, the mobility scenario is considered with a different speed of a mobile node ranging from very high to very low. The simulation results and an analytical model are compared with existing scheme for foglet selection by a mobile node. From the analysis and discussion, it is shown that the proposed system architecture helps in minimizing handover delay, packet loss, average queuing delay, and device lifetime. in a network.

In recent times, Plug-in Electric Vehicles (PEVs) have emerged as a new alternative to increase the efficiency of smart grids (SGs) in a vehicles-to-grid (V2G) environment. The V2G environment provides a bidirectional power and information flow, so that users can have an optimized usage as per their requirements. However, uncontrolled and unmanaged power distribution may lead to an overall performance degradation in V2G environment. One reason for this uncontrolled and unmanaged flow may be due to the usage of power by unauthorized users. To address this issue, we propose a Bayesian Coalition Negotiation Game (BCNG) as a utility for secure energy management for PEVs in the V2G environment. We have used a BCNG along with Learning Automata (LA), wherein LA are stationed on PEVs and are assumed as the players in the game. To provide an approach based on resilience for any misuse of electricity consumption, a new Secure Payoff Function (SPF) is proposed. The players take actions and update their action probability vector using the SPF. A Nash Equilibrium (NE) is also achieved in the game using convergence theory. Our proposal is evaluated with various metrics. The proposed scheme also provides mutual authentication and resilience against various attacks during power distribution.

Jongsung Kim, Bo Hong, Naveen Chilamkurti; Advanced Computer Technologies and Applications in Grid and Cloud Computing, The Computer Journal, Volume 57, Issue 2

In the past few years, cloud computing has emerged as a new reliable, scalable and flexible virtual computing environment (VCE). In this new VCE, users can use the available resources as a service by paying for that service according to the time for which these resources are used. It remains a significant challenge to achieve quality of service (QoS) in a VCE with the available resources. The main goal is to schedule the available resources so that the overall QoS delivered by the VCE can be improved. Resources are assumed to be located both at local and global sites. We propose a three-step scheme: resource selection, scheduling of users requests with shared resources and a new Resource Allocation and Adaptive Job Scheduling algorithm, which improves the QoS delivered by the cloud. For job scheduling, we define a new weight metric that is used to efficiently schedule jobs competing for available resources. Our proposed strategy increases the reliability of resource availability for a job and reduces the job completion time, which in turn increases the QoS delivered to end-users. We evaluate our proposed scheme using well-known heuristics. The results obtained show that our proposed scheme considerably reduces the job execution time, and increases the reliability of resource availability for job execution and throughput.

With the latest developments in cloud computing and Internet of Vehicles (IoV), now it is possible to construct an efficient next generation infrastructure, which may act as an interface for the connection of a number of objects such as vehicles, intelligent sensors, actuators, home appliances, high-computing servers, and computers to the Internet. In such an environment, vehicles on the road may act as source provider or consumer to facilitate various users connected to the Internet. Content distribution to all these objects especially to the vehicles in this environment is a challenging task due to the tight constraints of maintaining connectivity, coverage, and topology of the vehicles. To address these issues, in this paper, we proposed a new Bayesian coalition game (BCG) as-a-service for content distribution among these objects using support from cloud. We have addressed the problem of content distribution to vehicles from the perspective of BCG and learning automata (LA). Content are assumed to be located at the cloud, which is accessed by the vehicles through Internet even on-the-fly. Vehicles are assumed to be the players in the game and form a coalition among themselves using Markov decision process (MDP). For each action taken by an automaton, it may get a reward or a penalty from the environment according to which it updates its action probability vector. The performance of the proposed scheme is evaluated be selecting various parameters. The results obtained show that proposed scheme is effective in building next generation IoV environment.

This study proposes an efficient localization scheme in wireless sensor networks. The proposed scheme utilizes mobile anchors and is based on ring overlapping. In a wireless sensor network, the nodes that know their locations are called reference nodes, and the other nodes that are without the knowledge of their locations are called blind nodes. To localize a certain blind node, by comparing the relative RSSI (Received Signal Strength Indicator) values among nodes, mobile beacons are utilized to find out the rings that are centered at a reference node and contain the blind node. These rings are called B-Rings. Since the mobile anchors and the reference nodes know their own locations, the B-Rings can be precisely derived. Moreover, by using multiple mobile beacons, the widths of the B-Rings can be further minimized; and then by overlapping them, the location of the blind nodes can be efficiently estimated. Most existing localization schemes that utilize mobile anchors let the mobile anchors move randomly. In contrast, the proposed scheme provides regular and simple movement mechanisms for the mobile anchors. Thus, the mobile anchors consume less energy than the other schemes, in which the mobile anchors move randomly. Analytical analysis and simulation results show that the proposed localization mechanism can achieve better location accuracy as well as less movement length of the mobile anchor than the other existing related approaches.

When a wireless mesh network accommodates interactive applications with quality of service requirements, schedule-based protocols are more suitable than contention-based protocols. In this paper, the problem of determining an appropriate schedule assignment for multiple group transmissions within a spatial time division multiple access link scheduling network is referred to as an integrated multiple-group communication and link scheduling problem. A polynomial-time scheduling algorithm, designated as a source-parallel-aware assignment (SPAA), is proposed to increase the spatial utilisation within each time slot in order to enhance the network throughput. Furthermore, an advanced version of SPAA, designated as joint source-parallel-aware assignment with network coding (JSANC), is proposed to reduce the effects of bottleneck paths on the schedule frame length by flexibly applying conventional or opportunistic network coding approaches. Simulation results show that the proposed algorithms achieve a better network throughput than existing flow-based or particular order-based scheduling schemes.

In the past decade, as new wireless technologies are developed and deployed, they also need a new generation of security and privacy control techniques. Thus, security and privacy are becoming primary concerns. There are many security challenges ahead if wireless technologies are to gain the trust and confidence of users. Thus, this Special Issue on Security and Privacy in Wireless Systems aims to address many aspects of wireless communication security and covers advances in wireless communication systems that have enabled the Internet to be even more ubiquitous in terms of network deployment and management. This issue highlights some of the latest research results in this area and presents some novel and innovative security and privacy techniques especially used in Wireless Networks. This issue summarizes the current state-of-the-art research and provides valuable insights into future directions and challenges in the field. An eavesdropper can use reverse packet-routing to identify the location of the source sensor, and then capture the information. In “A Privacy-Aware Overlay Routing Scheme in WSNs,” L. Kazatzopoulos, K. Delakouridis, and G.F. Marias, introduced a novel approach that uses a non-geographical, overlay routing method for packet forwarding, routing, and delivery. By using enhanced information privacy and source-to-sink unlinkability, the authors conducted simulation experiments to assess the performance of their approach and compared this with related approaches. Topology Maintenance Protocols (TMPs) have been widely used in Wireless Sensor Networks (WSNs). Although different TMPs have been presented in the literature, few address security issues. Recently, a Secured TMP (Sec-TMP), which does not require pair-wise node confidentiality, has been proposed. In “Secure Topology Maintenance and Events Collection in WSN,” authors A. Gabrielli, M. Conti, R. Pietro, and V. Mancini investigated the performance of Sec-TMP without any assumption on the show-up time of the data-collecting node, nor on the mobility model. In particular, they tested Sec-TMP against a realistic, unpredictable, data-collecting mobility scenario. Their results suggest that Sec-TMP is effective and secure in a realistic, unpredictable and mobile environment. In a Wireless Sensor Network (WSN), the location of sensors is very critical since the monitored event can be detrimental if the location of the sensors is compromised and/or inaccurate. In “SecLoc- Secure Localization in WSNs Using CDS,” author A. Srinivasan proposed a novel localization method for WSNs, which exploits the connected dominating set property of a network graph. This proposed method uses a set of beacon nodes with a large resource base and assumes the role of dominant nodes. Using simulation results, the author confirms the efficiency and robustness of this model. In Vehicular Ad Hoc Networks (VANETs), message verification is not given much importance due to its excessive resource consumption. In “On Resource-Aware Message Verification in VANETs,” authors Z. Li and C. Chigan proposed a novel Resource Aware Message Versification (RAMV) scheme which streamlines existing message verification schemes to keep their resource consumption within the budget of the available resource for message verification. On the other hand, it also verifies that common security requirements for message verification are also properly met using several novel techniques. Position and velocity in VANETs play an important role. Forging such information can cause serve impact on both the performance and security of VANETs. In “Verifying Position and Velocity for Vehicular Ad-Hoc Networks,” authors H. D. Weerasinghe, R. Tackett, and H. Fu proposed a position and velocity verification scheme. This proposed scheme uses both the Global Positioning System (GPS) and Differential GPS (DGPS) to verify both the velocity and position of the vehicle. The proposed scheme is simulated using the NS-2 simulator to verify and test it in various robust and dynamic environments. We would like to take this opportunity to thank the Editor-in-chief of the Wiley Journal of Security and Communication Networks, Professor Hsiao-Hwa Chen, and all the anonymous reviewers who devoted much precious time reviewing all the papers submitted to this Journal. Their timely review and feedback helped us select the best papers included in this special issue. Last but not least, we would like to thank all authors who contributed to this special issue and the staff at Wiley for their support during its preparation. A Privacy-Aware Overlay Routing Scheme in WSNs by L. Kazatzopoulos, K. Delakouridis, and G.F. Marias. Secure Topology Maintenance and Events Collection in WSN by A. Gabrielli, M. Conti, R. Pietro and V. Mancini. SecLoc- Secure Localization in WSNs Using CDS by A. Srinivasan. On Resource-Aware Message Verification in VANETs by Z. Li and C. Chigan. Verifying Position and Velocity for Vehicular Ad-Hoc Networks by H. D. Weerasinghe, R. Tackett, and H. Fu.

Abstract The Internet has become a universal communication network tool. It has evolved from a platform that supports best‐effort traffic to one that now carries different traffic types including those involving continuous media with quality of service (QoS) requirements. As more services are delivered over the Internet, we face increasing risk to their availability given that malicious attacks on those Internet services continue to increase. Several networks have witnessed denial of service (DoS) and distributed denial of service (DDoS) attacks over the past few years which have disrupted QoS of network services, thereby violating the Service Level Agreement (SLA) between the client and the Internet Service Provider (ISP). Hence DoS or DDoS attacks are major threats to network QoS. In this paper we survey techniques and solutions that have been deployed to thwart DoS and DDoS attacks and we evaluate them in terms of their impact on network QoS for Internet services. We also present vulnerabilities that can be exploited for QoS protocols and also affect QoS if exploited. In addition, we also highlight challenges that still need to be addressed to achieve end‐to‐end QoS with recently proposed DoS/DDoS solutions. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract With the rapid growth of applications in Internet communication, the security for transmitting information on public network has become a fundamental issue. The Internet Protocol Security (IPsec) standard is developed by Internet Engineering Task Force (IETF) to provide the security services at the IP layer. IPSec solutions invariably result in a large‐packet size and a long processing time. Accordingly, this paper proposes new compression architecture, designated as Efficient Secure Pipe (ES_PIPE), to improve both the security and the performance of IPv6 networks. In contrast to traditional IPsec compression schemes, ES_PIPE provides a transport‐layer‐aware compression capability for different types of packets (e.g., TCP or UDP/RTP packets). The experimental results show that the proposed scheme reduces 20–30% transmission time compared to IPsec. Furthermore, ES_PIPE scheme yields about 20% improvement in the efficiency of the encryption and decryption processes. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract Delivering video streaming over wireless Internet is becoming increasingly popular. However, most of the research studies focused on the modeling analysis of system performance such as saturation throughput and channel utilization. Perceived quality of video streaming cannot be assessed solely based on the results of analytical models. In this paper, we propose a model to assess the perceived quality of MPEG‐4 video streaming over IEEE 802.11 distribution coordination function (DCF)‐based wireless local area networks. The analysis of our proposed model considers not only effects of losses such as collision loss from channel access competition but also wireless loss caused by wireless interferences. Moreover, the impact of the loss of specific MPEG‐4 video frames is also taken into account in the performance analysis. The model was validated by comparing our performance results with results obtained from simulation and analytical models. The results show that our proposed model is able to predict the perceived quality of MPEG‐4 video streaming over DCF‐based WLAN more accurately than other models. Copyright © 2010 John Wiley & Sons, Ltd.

These days, a wide variety of wireless interfaces are available to connect to Internet. When coverage area of these different technologies overlap, receiver equipped with multiple interfaces can use them simultaneously to improve the performance of its applications in terms of bandwidth rely on bandwidth aggregation. However, specific conditions such as bottleneck bandwidth and end-to-end delay need to be accounted for before using such techniques. If this problem of end-to-end delay and bottleneck bandwidth are not properly addressed, there may be many packets along multiple paths which can arrive late and can lead to a large number of out-of-order packets at the receiver, which can eventually cause serious degradation of video quality at the receiver. For this reason, in this study, the authors propose a multi-path transmission control scheme (MTCS) combining bandwidth aggregation and packet scheduling for real-time streaming in a multi-path environment. In a bandwidth aggregation scheme, the authors propose a mathematical model to find the transmission rate over each path in order to obtain the optimal total throughput. However, the end-to-end delay of each path is not the same. The out-of-order packets problem will become serious in a multi-path environment. Therefore the authors propose a packet scheduling scheme to arrange the transmission sequence in order to effectively minimise the impact of packet reordering at the receiver. Our proposed control scheme not only aggregates the available bandwidth of multiple paths, but also reduces the time of packet reordering at the receiver. Experimental results show with our proposed scheme, the authors not only obtain the optimal transmission throughput but also reduce packet reordering delays under varying drop and delay conditions caused by the underlying network.

Network Address Translation (NAT) alleviates the shortage of IPv4 addresses but incurs peer-to-peer communication, application functionality and packet integrity problems. To date, no approach has yet been proposed to solve these three problems. By exploiting mobile agent and active networking technologies, we propose a Programmable Network Address Translation (PNAT) implementation that enables peer-to-peer communication while maintaining application functionality and packet integrity. For peer-to-peer communication, our proposed PNAT approach works for various NAT types (including the Symmetric NAT) with simple APIs supported by our proposed NAT design. For application functionality, the PNAT uses the mobile code to update protocol information in packet payloads according to different application needs. For packet integrity, the PNAT allows applications to delay their data encryption until NAT begins to translate addresses and ports in packet headers. To validate our proposed PNAT approach, we implemented the PNAT design on Windows 2000, and we present an empirical performance evaluation of the implemented design.

The purpose of this paper is to study the packet loss effect on MPEG video transmission quality in wireless networks. First, we consider the distribution of packet losses in wireless network, including distributed and burst packet losses. Besides, we also discuss the additional packet drops by the play-out buffer at the received end, and the effect of the transmission packet size on the video delivered quality. From the results, we find that the effect of burst packet losses on the video delivered quality is less than distributed packet losses in the same packet loss rate. Moreover, the smaller size of the play-out buffer leads to more packet drops and worse video quality. Finally, if there is no video recovery for video transmission, the video delivered quality of the larger packet size will be better than smaller packet size.

The Internet has given rise to the proliferation of non-behaving flows that consume excess network bandwidth from behaving TCP flows. This has brought about the development of fair bandwidth sharing mechanisms at routers to deal with non-responsive flows. One such scheme that allocates bandwidth fairly to competing flows is core stateless fair queueing. This scheduling technique divides the network into edge routers that dominate the edge of the network and core routers that inhabit the interior of the network. However complexity contained at the edge of the network can prohibit the full-scale implementation of the scheme. We discuss the development of an alternative fair bandwidth-sharing mechanism that removes the edge router complexity imposed by CSFQ etc. and distributes bandwidth fairly amongst competing flows. To this end, we propose an algorithm known as source layered rate estimation (SLRE).

In this paper, the improvement of the quality of received video is demonstrated by applying priority dropping mechanism (PDM) to RED algorithm to protect the video layers selectively. Moreover, to achieve fairness among different types of network traffic with PDM, new packet classification scheme (PCS) is implemented to assign the priority to each SPLIT layer based upon the target rate. This PCS can also distinguish the priority for packets even within the same layer. In an effort to gauge the performance of the SPLIT protocol with the proposed packet classification scheme and to study the effects of PDM on the network, a number of experiments were conducted and compared.

In this paper, priority dropping mechanism (PDM) is applied to RED algorithm to protect the video layers selectively from performance and throughput deterioration. Moreover, to achieve fairness among different type of the network traffic with PDM, packet classification scheme (PCS) is implemented to assign the priority to each SPLIT layer or packet based upon the target rate.

This paper proposes a new receiver-based rate-adaptation protocol for multicasting video, called Split-Layer Video Multicast (SPLIT). Unlike existing receiver-based rate-adaptation protocols, such as Receiver-driven Layered Multicast (RLM), the SPLIT protocol is specifically designed to take advantage of existing packet loss concealment techniques to provide end-users with increased quality of video. In an effort to gauge the performance of the SPLIT protocol, a number of experiments using the NS-2 network simulator were conducted and the results were compared with those of the RLM protocol. The results show that the proposed SPLIT protocol utilizes the available bandwidth in a more efficient way than the RLM protocol does.

STAIR (simulated TCP's additive increase/multiplicative decrease with rate-basis) is a multicast congestion control algorithm involving both cumulative and non-cumulative layers. We have simulated STAIR with multimedia traffic to measure stability, fairness, scalability, and heterogeneity. Our simulation results clearly conclude that STAIR exhibits a high degree of fairness for CBR, but fails to do so with VBR traffic.