With the arrival of B-ISDN, widespread usage of multicast services such as TV broadcasting and video 900 services will increase the possibility of network congestion unless efficient multiple destination routing (MDR) algorithms are used. Current MDR algorithms using link cost based on bandwidth usage or distance to compute the minimum cost routing tree do not take into account the vast amount of information collected by intelligent network (IN) databases. In this paper, we propose a multicast routing algorithm which modifies the way the cost is calculated by using the predicted traffic statistics collected by IN databases. We also show that the traffic handling characteristics vastly improved over conventional MDR algorithms.

This paper focuses on learning the economic behaviour of the access point (AP) and users in wireless local area networks (WLANs), and using a game theoretic approach to analyze the interactions among them. Recent studies have shown that the AP would adopt a simple, yet optimal, fixed rate pricing strategy when the AP has an unlimited uplink bandwidth to the Internet and the channel capacity of WLAN is unlimited. However, the fixed rate strategy fails to be optimal if a more realistic model with limited capacity is considered. A substitute pricing scheme for access service provisioning is hence proposed. In particular, the AP first estimates the probable utility degradation of existing users consequent upon the admission of an incoming user. Second, the AP decides: (i) whether the incoming user should be accepted; and (ii) the price to be announced in order to try to maximize the overall revenue. The condition, under which the proposed scheme results in a perfect Bayesian equilibrium (PBE), is investigated.

Traditional traffic analysis is can be performed online only when detection targets are well specified and are fairly primitive. Local processing at measurement point is discouraged as it would considerably affect major functionality of a network device. When traffic is analyzed at flow level, the notion of flow timeout generates differences in flow lifespan and impedes unbiased monitoring, where only n-top flows ordered by a certain metric are considered. This paper proposes an alternative manner of traffic analysis based on source IP aggregation. The method uses flows as basic building blocks but ignores timeouts, using short monitoring intervals instead. Multidimensional space of metrics obtained through IP aggregation, however, enhances capabilities of traffic analysis by facilitating detection of various anomalous conditions in traffic simultaneously.

Multicast routing with Quality-of-Service (QoS) guarantees is the key to efficient content distribution and sharing. Developing QoS-aware multicast routing algorithm is an important open topic. This paper investigates QoS-aware multicast routing problem with K constraints where K > 2. The contributions made in this paper include a heuristic that employs the concept of nonlinear combination to extend the existing well-known algorithm for fast computation of a QoS multicast tree, and a Fully Polynomial Time Approximation Scheme (FPTAS) to approximate a multicast routing tree with QoS guarantees. The theoretical analyses and simulations conducted on both algorithms show that the algorithms developed in this paper are general and flexible, thus are applicable to the various networking systems.

This paper proposes a new dynamic multicast routing algorithm for layered streams. Since a layered multicast technique accommodates different types of users in the same multicast group, it helps to provide multicast services in a heterogeneous environment. However, this makes it difficult to construct an efficient routing tree when receivers join or leave a multicast session dynamically. In the proposed algorithm, we adopt a pre-determined path approach to handle such dynamic membership of a layered multicast session without the burden of much additional traffic. Simulation results show that the proposed algorithm can minimize the average multicast tree cost, and that it works well on large-scale networks and those with traffic heterogeneity and a small number of routing control messages.

This paper studies a video storage problem that occurs in Video-on-Demand (VOD) networks and in other distributed database systems. Videos should be stored in order to respect various constraints, especially available storage and transmission capacities. We show there exists an algorithm to solve this combinatorial problem through a pricing mechanism and that it converges to a solution under some general conditions. Simulation results with up to 43-node networks and up to 300 videos show that the algorithm is fast.

It is believed that the wavelength switched optical network (WSON) technology is moving towards being adopted by large-scale networks. Wavelength conversion and signal regeneration through reamplifying, reshaping, and retiming (3R) are beneficial to support the expansion of WSON. In many cases, these two functions can be technically integrated into a single shared physical component, namely the wavelength convertible 3R regenerator (WC3R). However, fully deploying such devices is infeasible due to their excessive cost. Thus, this topic serves as a motivation behind the investigation of the sparse placement issue of WC3Rs presented in this paper. A series of strategies are proposed based on knowledge of the network. Moreover, a novel adaptive routing and joint resource assignment algorithm is presented to provision the lightpaths in WSON with sparsely placed WC3Rs. Extensive simulation trials are conducted under even and uneven distribution of WC3R resource. Each strategic feature is examined for its efficiency in lowering the blocking probability. The results reveal that carefully designed sparse placement of WC3Rs can achieve performance comparable to that of full WC3R placement scenario. Furthermore, the expenditure of WC3R deployment also depends on the type of used WC3Rs characterized by the wavelength convertibility, i.e., fixed WC3R or tunable WC3R. This paper also investigates WSON from the perspective of cost and benefit by employing different types of WC3Rs in order to find the possibility of more efficient WC3R investment.

WDM optical networks represent the future direction of high capacity wide-area network applications. By creating optical paths between several nodes in the core networks, a logical topology can be created over the physical topology. By reconfiguring the logical topology, network resource utilization can be optimized corresponding to traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. In this paper we consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balancing between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually represented as Mixed Integer Linear Programming, but it grows intractable with increasing network size. Here we propose a simulated annealing approach in order to both determine the target topology with a smaller logical topology change and also satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity. This is achieved by tuning this threshold to a feasible value. For effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.

Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.

With conventional dynamic routing algorithms, many query messages are required in a distributed environment for efficient multicast routing of any traffic volume. We have developed a dynamic routing algorithm that uses a predetermined path search in which an appropriate multicast path is dynamically constructed by searching only a few nodes. This algorithm can construct an efficient multicast tree for any traffic volume. Simulation has shown that the proposed algorithm is advantageous compared with conventional dynamic routing algorithms when nodes are added to or removed from the multicast group during steady-state simulation.

In NGN standards, End Host, also referred to as Terminal Equipment (TE), holds an important place in end-to-end path performance. However, most researchers neglect TE performance when considering performance of end-to-end paths. As far as the authors' knowledge goes, no previous study has proposed a model for TE performance. This paper proposes a method for measuring performance of TE and model extraction based on measurement data. The measurement was made possible with the use of a special NPU (Network Processing Unit) implemented as a programmable NIC. Along with the probing itself, a framework for removing the skew between the NPU and OS is developed in this paper. The multidimensional analysis includes method of probing, packet size and background traffic volume, and studies their effect on TE performance. A method for extracting a generic TE model is proposed. The outcome of this research can be used for modelling TE in simulations and in modelling end-to-end performance when considering QoS in NGN.

The demand for wireless traffic is increasing rapidly, which has posed huge challenges to mobile network operators (MNOs). A heterogeneous network (HetNet) framework, composed of a marcocell and femtocells, has been proved to be an effective way to cope with the fast-growing traffic demand. In this paper, we assume that both the macrocell and femtocells are owned by the same MNO, with revenue optimization as its ultimate goal. We aim to propose a pricing strategy for macro-femto HetNets with a user centric vision, namely, mobile users would have their own interest to make rational decisions on selecting between the macrocell and femtocells to maximize their individual benefit. We formulate a Stackelberg game to analyze the interactions between the MNO and users, and obtain the equilibrium solution for the Stackelberg game. Via extensive simulations, we evaluate the proposed pricing strategy in terms of its efficiency with respect to the revenue optimization.

An architecture is presented for efficient and reliable delivery of multimedia contents from a primary center (PC) to secondary centers (SCs). Requested contents are delivered from the PC to the SCs through a satellite broadcast channel, or from one SC to another SC through a terrestrial channel. Cycling methods are presented that enable sharing of the contents directory of each SC. Several fundamental models and algorithms are introduced for possible consideration during the planning and design of a contents-delivery system. Simulation has shown that using both satellite broadcast and terrestrial channels for contents delivery is superior in terms of cost to the conventional use of only a satellite network.

This paper describes the voice-data hybrid transmission facilities, which can be obtained by using 64 kbit/sec digital line. Instead of using separate transmission facilities for voice and data services, or instead of increasing the digital transmission rate, the silent portion of telephonic speech can be used to transmit the data. The line is available for the data transmission when a pause of the voice is detected, and the line is blocked for the data transmission during a talkspurt of the voice. Two models of the hybrid transmission system are shown. The first model, in which the data arrive randomly in bursts, is useful to describe a kind of interactive process. The second model, in which the data arrive continuously, describes file transfers, facsimile transmissions, etc. The necessary buffers, the blocking probabilities, the data delay, and other factors of both models are calculated.

Network traffic load usually differs significantly at different times of a day due to users' different time-preference. Network congestion may happen in traffic peak times. In order to prevent this from happening, network service providers (NSPs) can either over-provision capacity for demand at peak times of the day, or use dynamic time-dependent pricing (TDP) scheme to reduce the demand at traffic peak times. Since over-provisioning network capacity is costly, many researchers have proposed TDP schemes to control congestion as well as to improve the revenue of NSPs. To the best of our knowledge, all the studies on TDP schemes consider only the monopoly or duopoly NSP case. In our previous work, the duopoly NSP case has been studied with the assumption that each NSP has complete information of quality of service (QoS) of the other NSP. In this paper, an oligopoly NSP case is studied. NSPs try to maximize their overall revenue by setting time-dependent price, while users choose NSPs by considering their own time preference, congestion status in the networks and the price set by the NSPs. The interactions among NSPs are modeled as an oligopoly Bertrand game. Firstly, assuming that each NSP has complete information of QoS of all NSPs, a unique Nash equilibrium of the game is established under the assumption that users' valuation of QoS is uniformly distributed. Secondly, the assumption of complete information of QoS of all NSPs is relaxed, and a learning algorithm is proposed for NSPs to achieve the Nash equilibrium of the game. Analytical and experimental results show that NSPs can benefit from TDP scheme, however, not only the competition effect but also the incomplete information among NSPs causes revenue loss for NSPs under the TDP scheme.

Distributed Web caching allows multiple clients to quickly access a pool of popular Web pages. Conventional distributed Web caching schemes, e. g. , the Internet cache protocol and hash routing, require the sending of many query messages among cache servers and/or impose a large load on the cache servers when they are widely dispersed. To overcome these problems, we propose a hash-based query caching method using both a hash function and a query caching method. This method can find cached objects among several cache servers by using only one query message, enabling the construction of an efficient large-scale distributed Web cache server. Compared to conventional methods, this method reduces cache server overhead and object retrieval latency.

In ad hoc networks, broadcast forwarding protocols called OR (opportunistic routing) have been proposed to gain path diversity for higher packet delivery rates and shorter end-to-end delays. In general backoff-based OR protocols, each receiver autonomously makes a forwarding decision by using certain metrics to determine if a random backoff time is to be applied. However, each forwarder candidate must wait for the expiration of the backoff timer before forwarding a packet. Moreover, they cannot gain path diversity if the forwarding path includes local sparse areas, and this degrades performance as it strongly depends on the terminal density. In this paper, we propose a novel OR protocol called PRIOR (prioritized forwarding for opportunistic routing). In PRIOR, a terminal, called a prioritized forwarder and which forwards packets without using a backoff time, is selected from among the neighbours. In addition, PRIOR uses lightweight hop-by-hop retransmission control to mitigate the effect of terminal density. Moreover, we introduce an enhancement to PRIOR to reduce unnecessary forwarding by using an explicit acknowledgement. We evaluate PRIOR in comparison with conventional protocols in computer simulations.

This paper studies the impact of integrating pricing with connection admission control (CAC) on the congestion management practices in contention-based wireless random access networks. Notably, when the network is free of charge, each self-interested user tries to occupy the channel as much as possible, resulting in the inefficient utilization of network resources. Pricing is therefore adopted as incentive mechanism to encourage users to choose their access probabilities considering the real-time network congestion level. A Stackelberg leader-follower game is formulated to analyze the competitive interaction between the service provider and the users. In particular, each user chooses the access probability that optimizes its payoff, while the self-interested service provider decides whether to admit or to reject the user's connection request in order to optimize its revenue. The stability of the Stackelberg leader-follower game in terms of convergence to the Nash equilibrium is established. The proposed CAC scheme is completely distributed and can be implemented by individual access points using only local information. Compared to the existing schemes, the proposed scheme achieves higher revenue gain, higher user payoff, and higher QoS performance.

Multicasting is a remarkable technology that can effectively provide point-to-multipoint communications. The multicast communication can substantially decrease traffic in a network and thus save network resources and transmission costs. If multicasting is applied to a content delivery system, however, the transmission speed must be set to the lowest one among the available capacities of links on the multicast tree for all client terminals to receive the contents simultaneously. This type of problem is especially serious for heterogeneous networks. This paper studies effective content delivery systems for non-real-time point-to-multipoint services over heterogeneous environments and proposes an adaptive delivery system to select multicasting and store-and-forward transferring data streams. The results obtained by computer simulation show that our proposed system can reduce delivery time and that it is scalable to large networks and robust against variations in network size as well as environmental heterogeneities.