We examine delay performance of packets from constant bit rate (CBR) traffic whose delay is affected by non-real-time traffic. The delay performance is analyzed by solving the Σ Di/G/1 queue with vacations. Our analysis allows heterogeneous service time and heterogeneous interarrival time. Thus, we can get the impact of packet length of a stream on the delay time of other streams. We then give various numerical results for enterprise multimedia networks, which include voice, video and data communication services. From our quantitative evaluation, we conclude that packet length of video traffic has large influence on the delay time of voice traffic while voice traffic gives a little impact on the delay time of video traffic.

Wireless networked control systems (WNCSs) are control systems whose components are connected through wireless networks. In WNCSs, a controlled object (CO) could become unstable due to bursty packet losses in addition to random packet losses and round-trip delays on wireless networks. In this paper, to reduce these network-induced effects, we propose a new design for multihop TDMA-based WNCSs with two-disjoint-path switching, where two disjoint paths are established between a controller and a CO, and they are switched if bursty packet losses are detected. In this system, we face the following two difficulties: (i) link scheduling in TDMA should be done in such a way that two paths can be switched without rescheduling, taking into account of the constraint of control systems. (ii) the conventional cross-layer design method of control systems is not directly applicable because round-trip delays may vary according to the path being used. Therefore, to overcome the difficulties raised by the two-path approach, we reformulate link scheduling in multihop TDMA and cross-layer design for control systems. Simulation results confirm that the proposed WNCS achieves better performance in terms of the 2-norm of CO's states.

Custody transfer in delay tolerant networks (DTNs) provides reliable end-to-end data delivery by delegating the responsibility of data transfer among special nodes (custodians) in a hop-by-hop manner. However, storage congestion occurs when data increases and/or the network is partitioned into multiple sub-networks for a long time. The storage congestion can be alleviated by message ferries which move around the network and proactively collect data from the custodians. In such a scenario, data should be aggregated to some custodians so that message ferries can collect them effectively. In this paper, we propose a scheme to aggregate data into selected custodians, called aggregators, in a fully distributed and autonomous manner with the help of evolutionary game theoretic approach. Through theoretical analysis and several simulation experiments, taking account of the uncooperative behavior of nodes, we show that aggregators can be selected in a self-organized manner and the number of aggregators can be controlled to a desired value.

Epidemic Routing is a data delivery scheme based on the store-carry-forward routing paradigm for sparsely populated mobile ad hoc networks. In Epidemic Routing, each node copies packets in its buffer into any other node that comes within its communication range. Although Epidemic Routing has short delay performance, it causes excessive buffer space utilization at nodes because many packet copies are disseminated over the network. In this paper, aiming at efficient buffer usage, we propose an XOR-based delivery scheme for Epidemic Routing, where nodes encode packets by XORing them when their buffers are full. Note that existing delivery schemes with coding are active coding, where source nodes always encode packets before transmitting them. On the other hand, the proposed scheme is passive coding, where source nodes encode packets only when buffer overflow would occur. Therefore, the behavior of the proposed scheme depends on the buffer utilization. More specifically, if sufficient buffer space is available, the proposed scheme delivers packets by the same operation as Epidemic Routing. Otherwise, it avoids buffer overflow by encoding packets. Simulation experiments show that the proposed scheme improves the packet delivery ratio.

To diffuse multimedia information services, communication networks must guarantee the quality of services (QoSs) requested by users. In addition, users should be allowed to observe the network in order to customize their own services. A new network management architecture is therefore essential. It must perceive not only node connectivity, but also network failure points and the traffic situation dynamically. This paper introduces the network map as such an architecture on personalized multimedia communication networks and proposes multiple QoS routing using the network map. Moreover, a prototype system is built in order to verify the availability of the network map.

In the Internet, because of huge scale and distributed administration, it is of practical importance to infer network-internal characteristics that cannot be measured directly. In this paper, based on a general framework we proposed previously, we present a feasible method of inferring packet loss rates of individual links from end-to-end measurement of unicast probe packets. Compared with methods using multicast probes, unicast-based inference methods are more flexible and widely applicable, whereas they have a problem with imperfect correlation in concurrent events on paths. Our method can infer link loss rates under this problem, and is applicable to various path-topologies including trees, inverse trees and their combinations. We also show simulation results which indicate potential of our unicast-based method.

We propose a new network architecture nemed Holonic Network for personalized multimedia communications, which is characterized by distributed cooperative networking based on autonomous management and all-optical transport networks. We than propose autonomous routing method. Moreover, an information searching method and a route generation method with network maps, which are essential for this network, are proposed. Lastly, we evaluate the proposed network performance by theoretical analysis and system emulation.

This paper proposes a contention-free burst scheduling scheme for optically burst-switched WDM networks. We construct contention-free wavelength planes (λ-planes) by assigning dedicated wavelengths to each ingress node. Bursts are transmitted to their egress nodes on λ-planes, along routes forming a spanning tree. As a result, contention at intermediate core nodes is completely eliminated, and contention at ingress nodes is resolved by means of electric buffers. This paper develops a spanning tree construction algorithm, aiming at balancing input loads among output ports at each ingress node. Furthermore, a wavelength assignment algorithm is proposed, which is based on the amount of traffic lost at ingress nodes. We show that the proposed scheme can decrease the burst loss probability drastically, even if traffic intensities at ingress nodes are different.

We consider a location-aware store-carry-forward routing scheme based on node density estimation (LA Routing in short), which adopts different message forwarding strategies depending on node density at contact locations where two nodes encounter. To do so, each node estimates a node density distribution based on information about contact locations. In this paper, we clarify how the estimation accuracy affects the performance of LA Routing. We also examine the performance of LA Routing when it applies to networks with homogeneous node density. Through simulation experiments, we show that LA Routing is fairly robust against the accuracy of node density estimation and its performance is comparable with Probabilistic Routing even in the case that that node density is homogeneous.

The MapReduce job scheduler implemented in Hadoop is a mechanism to decide which job is allowed to use idle resources in Hadoop. In terms of the mean job response time, the performance of the job scheduler strongly depends on the job arrival pattern, which includes job size (i.e., the amount of required resources) and their arrival order. Because existing schedulers do not utilize information about job sizes, however, those schedulers suffer severe performance degradation with some arrival patterns. In this paper, we propose a scheduler that estimates and utilizes remaining job sizes, in order to achieve good performance regardless of job arrival patterns. Through simulation experiments, we confirm that for various arrival patterns, the proposed scheduler achieves better performance than the existing schedulers.

In this paper, we study robust Principal Component Analysis (PCA)-based anomaly detection techniques in network traffic, which can detect traffic anomalies by projecting measured traffic data onto a normal subspace and an anomalous subspace. In a PCA-based anomaly detection, outliers, anomalies with excessively large traffic volume, may contaminate the subspaces and degrade the performance of the detector. To solve this problem, robust PCA methods have been studied. In a robust PCA-based anomaly detection scheme, outliers can be removed from the measured traffic data before constructing the subspaces. Although the robust PCA methods are promising, they incure high computational cost to obtain the optimal location vector and scatter matrix for the subspace. We propose a novel anomaly detection scheme by extending the minimum covariance determinant (MCD) estimator, a robust PCA method. The proposed scheme utilizes the daily periodicity in traffic volume and attempts to detect anomalies for every period of measured traffic. In each period, before constructing the subspace, outliers are removed from the measured traffic data by using a location vector and a scatter matrix obtained in the preceding period. We validate the proposed scheme by applying it to measured traffic data in the Abiline network. Numerical results show that the proposed scheme provides robust anomaly detection with less computational cost.

Network tomography is a technique for estimating internal network characteristics from end-to-end measurements. In this paper, we focus on loss tomography, which is a network tomography problem for estimating link loss rates. We study a loss tomography problem to detect links with high link loss rates in network environments with dynamically changing link loss rates, and propose a window-based sequential loss tomography scheme. The loss tomography problem is formulated as an underdetermined linear inverse problem, where there are infinitely many candidates of the solution. In the proposed scheme, we use compressed sensing, which can solve the problem with a prior information that the solution is a sparse vector. Measurement nodes transmit probe packets on measurement paths established between them, and calculate packet loss rates of measurement paths (path loss rates) from probe packets received within a window. Measurement paths are classified into normal quality and low quality states according to the path loss rates. When a measurement node finds measurement paths in the low quality states, link loss rates are estimated by compressed sensing. Using simulation scenarios with a few link states changing dynamically from low to high link loss rates, we evaluate the performance of the proposed scheme.

This survey summarizes the state-of-the-art research on network coding, mainly focusing on its applications to computer networking. Network coding generalizes traditional store-and-forward routing techniques by allowing intermediate nodes in networks to encode several received packets into a single coded packet before forwarding. Network coding was proposed in 2000, and since then, it has been studied extensively in the field of computer networking. In this survey, we first summarize linear network coding and provide a taxonomy of network coding research, i.e., the network coding design problem and network coding applications. Moreover, the latter is subdivided into throughput/capacity enhancement, robustness enhancement, network tomography, and security. We then discuss the fundamental characteristics of network coding and diverse applications of network coding in details, following the above taxonomy.

In this paper, we consider network monitoring techniques to estimate communication qualities in wide-area mobile networks, where an enormous number of heterogeneous components such as base stations, routers, and servers are deployed. We assume that average delays of neighboring base stations are comparable, most of servers have small delays, and delays at core routers are negligible. Under these assumptions, we propose Heterogeneous Delay Tomography (HDT) to estimate the average delay at each network component from end-to-end round trip times (RTTs) between mobile terminals and servers. HDT employs a crowdsourcing approach to collecting RTTs, where voluntary mobile users report their empirical RTTs to a data collection center. From the collected RTTs, HDT estimates average delays at base stations in the Graph Fourier Transform (GFT) domain and average delays at servers, by means of Compressed Sensing (CS). In the crowdsourcing approach, the performance of HDT may be degraded when the voluntary mobile users are unevenly distributed. To resolve this problem, we further extend HDT by considering the number of voluntary mobile users. With simulation experiments, we evaluate the performance of HDT.

We propose a home base-aware store-carry-forward routing scheme using location-dependent utilities of nodes, which adopts different message forwarding strategies depending on location where nodes encounter. Our routing scheme first attempts to deliver messages to its home base, the area with the highest potential for the presence of the destination node in the near future. Once a message copy reaches its home base, message dissemination is limited within the home base, and nodes with message copies wait for encountering the destination node. To realize our routing scheme, we use two different utilities of nodes depending on location: Outside the home base of a message, nodes approaching to the home base have high utility values, while within the home base, nodes staying the home base have high utility values. By using these utilities properly, nodes with message copies will catch the destination node “by ambush” in the home base of the destination node. Through simulation experiments, we demonstrate the effectiveness of our routing scheme.

Recent improvements in the performance of end-computers and networks have made it feasible to construct a grid system over the Internet. A grid environment consists of many computers, each having a set of components and a distinct performance. These computers are shared among many users and managed in a distributed manner. Thus, it is important to focus on a situation in which the computers are used unevenly due to decentralized management by different task schedulers. In this study, which is a preliminary investigation of the performance of task allocation schemes employed in a decentralized environment, the average execution time of a long-lived task is analytically derived using the M/G/1-PS queue. Furthermore, assuming a more realistic condition, we evaluate the performance of some task allocation schemes adopted in the analysis, and clarify which scheme is applicable to a realistic grid environment.

The layer3 switch enables us to fast transmit IP datagrams using the cut-through technique. The current layer3 router would become bottleneck in terms of delay performance as the amount of traffic injected into high speed networks gets relatively large. Thus, the layer3 switch should be an important element constructing the next generation Internet backbone. In this paper, we analyze the cut-through rate, the datagram waiting time and the mis-ordered rate of a layer3 switch in case of flow-driven connection setup. In the analysis, by using 3-state Markov modulated Bernoulli process (MMBP), we model the arrival process of IP flow and IP datagram from each source. Furthermore, we investigate impacts of the arrival rate and the average datagram length on the performance.

In future high-speed networks, provision of diverse multimedia services with strict quality-of-service (QoS) requirements, such as bandwidth, delay and so on, is desired. QoS routing is a possible solution to handle these services. Generally, a path selection for QoS routing is formulated as a shortest path problem subject to multiple constraints. However, it is known to be NP-complete when more than one QoS constraint is imposed. As a result, many heuristic algorithms have been proposed so far. The authors proposed a path selection algorithm Fallback+ for QoS routing, which focuses not only on the path selection with multiple constraints but also on the efficient use of network resources. This paper proposes an enhanced version of Fallback+, named Enhanced Fallback+, where in a shrewd way, it keeps tentative paths produced in the conventional Fallback algorithm with Dijkstra's algorithm. Simulation experiments prove the excellent performance of Enhanced Fallback+, compared with the original Fallback+ and other existing path selection algorithms.

This paper studies the local Poisson property of aggregated IP traffic. First, it describes the scenario where IP traffic presents a Poisson-like characteristic within some limited range of time scales when packets from independent traffic streams are aggregated. Each of the independent traffic streams corresponds to a series of correlated IP packets such as those of a transport connection. Since the Poisson-like characteristic is observed only within some limited range of time scales, we call this characteristic the local Poisson property. The limited range of time scales of the local Poisson property can be estimated from a network configuration and characteristics of transport connections. Second, based on these observations, we seek the possibility to apply an ordinary Poisson process to evaluation of the packet loss probability in IP networks. The analytical investigation, where IP traffic is modeled by a superposition of independent branching Poisson processes that presents the local Poisson property, suggests that the packet loss probability can be estimated by a finite-buffer queue with a Poisson process when the buffer size is within a certain range. The investigation is verified by simulations. These findings expand the applicability of conventional Poisson-based approaches to IP network design issues.

In the IEEE 802.11 MAC protocol, access points (APs) are given the same priority as wireless terminals in terms of acquiring the wireless link, even though they aggregate several downlink flows. This feature leads to a serious throughput degradation of downlink flows, compared with uplink flows. In this paper, we propose a dynamic contention window control scheme for the IEEE 802.11e EDCA-based wireless LANs, in order to achieve fairness between uplink and downlink TCP flows while guaranteeing QoS requirements for real-time traffic. The proposed scheme first determines the minimum contention window size in the best-effort access category at APs, based on the number of TCP flows. It then determines the minimum and maximum contention window sizes in higher priority access categories, such as voice and video, so as to guarantee QoS requirements for these real-time traffic. Note that the proposed scheme does not require any modification to the MAC protocol at wireless terminals. Through simulation experiments, we show the effectiveness of the proposed scheme.