The proxy mechanism widely used in WWW systems offers low-delay data delivery by means of "proxy server." By applying proxy mechanisms to video streaming system, we expect that high-quality and low-delay video distribution can be accomplished without introducing extra load on the system. In addition, it is effective to adapt the quality of cached video data appropriately in the proxy if user requests are diverse due to heterogeneity in terms of the available bandwidth, end-system performance, and user's preferences on the perceived video quality. In this paper, we propose proxy caching mechanisms to accomplish high-quality and low-delay video streaming services. In our proposed system, a video stream is divided into blocks for efficient use of cache buffer. A proxy cache server is assumed to be able to adjust the quality of cached or retrieved video blocks to requests through video filters. We evaluate our proposed mechanisms in terms of the required buffer size, the play-out delay and the video quality through simulation experiments. Furthermore, to verify the practicality of our mechanisms, we implement our proposed mechanisms on a real system and conducted experiments. Through evaluations from several performance aspects, it is shown that our proposed mechanisms can provide users with a low-latency and high-quality video streaming service in a heterogeneous environment.

Communication among isolated networks (clusters) in delay tolerant networks (DTNs) can be supported by a message ferry, which collects bundles from clusters and delivers them to a sink node. When there are lots of distant static clusters, multiple message ferries and sink nodes will be required. In this paper, we aim to make groups, each of which consists of physically close clusters, a sink node, and a message ferry. Our objective is minimizing the overall mean delivery delay of bundles in consideration of both the offered load of clusters and distances between clusters and their sink nodes. Based on existing work, we first model this problem as a nonlinear integer programming. Using a commercial nonlinear solver, we obtain a quasi-optimal grouping. Through numerical evaluations, we show the fundamental characteristics of grouping, the impact of location limitation of base clusters, and the relationship between delivery delay and the number of base clusters.

Traffic congestion in road networks has been studied as the congestion game in game theory. In the existing work, the road usage by each agent was assumed to be static during the whole time horizon of the agent's travel, as in the classical congestion game. This assumption, however, should be reconsidered because each agent sequentially uses roads composing the route. In this paper, we propose a multi-agent distributed route selection scheme based on a gradient descent method considering the time-dependency among agents' road usage for vehicular networks. The proposed scheme first estimates the time-dependent flow on each road by considering the agents' probabilistic occupation under the first-in-first-out (FIFO) policy. Then, it calculates the optimal route choice probability of each route candidate using the gradient descent method and the estimated time-dependent flow. Each agent finally selects one route according to the optimal route choice probabilities. We first prove that the proposed scheme can exponentially converge to the steady-state at the convergence rate inversely proportional to the product of the number of agents and that of individual route candidates. Through simulations under a grid-like network and a real road network, we show that the proposed scheme can improve the actual travel time by 5.1% and 2.5% compared with the conventional static-flow based approach, respectively. In addition, we demonstrate that the proposed scheme is robust against incomplete information sharing among agents, which would be caused by its low penetration ratio or limited transmission range of wireless communications.

The Proof of Stake (PoS) protocol is one of the consensus algorithms for blockchain, in which the integrity of a new block is validated according to voting by nodes called validators. However, due to validator-oriented voting, voting results are likely to be false when the number of validators with wrong votes increases. In the PoS protocol, validators are motivated to vote correctly by reward and penalty mechanisms. With such mechanisms, validators who contribute to correct consensuses are rewarded, while those who vote incorrectly are penalized. In this paper, we consider an incentivization mechanism based on the voting profile of a validator, which is estimated from the voting history of the validator. In this mechanism, the stake collected due to the penalties are redistributed to validators who vote correctly, improving the incentive of validators to contribute to the system. We evaluate the performance of the proposed mechanism by computer simulations, investigating the impacts of system parameters on the estimation accuracy of the validator profile and the amount of validator's stake. Numerical results show that the proposed mechanism can estimate the voting profile of a validator accurately even when the voting profile dynamically changes. It is also shown that the proposed mechanism gives more reward to validators who vote correctly with high voting profile.

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.

Mobile Ad Hoc Networks (MANETs) are temporal and infrastructure-independent wireless networks that consist of mobile nodes. For instance, a MANET can be used as an emergent network for communication among people when a disaster occurred. Since there is no central server in the network, each node has to find out its desired information (objects) by itself. Constructing a mobile Peer-to-Peer (P2P) network over the MANET can support the object search. Some researchers proposed construction schemes of mobile P2P networks, such as Ekta and MADPastry. They integrated DHT-based application-layer routing and network-layer routing to increase search efficiency. Furthermore, MADPastry proposed a clustering method which groups the overlay nodes according to their physical distance. However, it has also been pointed out that the search efficiency deteriorates in highly dynamic environments where nodes quickly move around. In this paper, we focus on route disappearances in the network layer which cause the deterioration of search efficiency. We describe the detail of this problem and evaluate quantitatively it through simulation experiments. We extend MADPastry by introducing a method sharing objects among nodes in a cluster. Through simulation experiments, we show that the proposed method can achieve up to 2.5 times larger success rate of object search than MADPastry.

Wireless mesh networks have been attracting many users in recent years. By connecting base stations (mesh nodes) with wireless connections, these network can achieve a wide-area wireless environment with flexible configuration and low cost at the risk of radio interference between wireless links. When we utilize wireless mesh networks as infrastructures for Internet access, all network traffic from mobile nodes goes through a gateway node that is directly connected to the wired network. Therefore, it is necessary to distribute the traffic load by deploying multiple gateway nodes. In this paper, we propose a spanning tree construction algorithm for TDMA-based wireless mesh networks with multiple gateway nodes so as to maximize the traffic volume transferred between the mesh network and the Internet (system throughput) by taking account of the traffic load on the gateway nodes, the access link capacity and radio interference. Through a performance evaluation, we show that the proposed algorithm increases the system throughput regardless of the bottleneck position and achieves up to 3.1 times higher system throughput than a conventional algorithm.

To establish a network service in network functions virtualization (NFV) networks, the orchestrator addresses the challenge of service chaining and virtual network function placement (SC-VNFP) by mapping virtual network functions (VNFs) and virtual links onto physical nodes and links. Unlike traditional networks, network operators in NFV networks must contend with both hardware and software failures in order to ensure resilient network services, as NFV networks consist of physical nodes and software-based VNFs. To guarantee network service quality in NFV networks, the existing work has proposed an approach for the SC-VNFP problem that considers VNF diversity and redundancy. VNF diversity splits a single VNF into multiple lightweight replica instances that possess the same functionality as the original VNF, which are then executed in a distributed manner. VNF redundancy, on the other hand, deploys backup instances with standby mode on physical nodes to prepare for potential VNF failures. However, the existing approach does not adequately consider the tradeoff between resource efficiency and service availability in the context of VNF diversity and redundancy. In this paper, we formulate the SC-VNFP problem with VNF diversity and redundancy as a two-step integer linear program (ILP) that adjusts the balance between service availability and resource efficiency. Through numerical experiments, we demonstrate the fundamental characteristics of the proposed ILP, including the tradeoff between resource efficiency and service availability.

Peer-to-Peer (P2P) file distribution systems can efficiently disseminate massive contents, such as disk images of operating systems, from a server to many users in a piece-by-piece manner. In particular, the BitTorrent protocol optimizes each peer's download speed by applying the tit-for-tat (TFT) strategy, where each peer preferentially uploads piece(s) to peer(s) from which it can download missing pieces faster. To the best of our knowledge, however, the optimality of TFT-based P2P file distribution has not been studied sufficiently. In this paper, we aim to understand the optimal scheduling in TFT-based P2P file distribution. First, we develop a discrete-time model of TFT-based P2P file distribution and formulate its optimal scheduling as a two-step integer linear programming problem. The first step is to minimize the average file retrieval time among peers, and the second step is to improve fairness among peers. We analyze the optimal solution obtained by the existing solver and reveal the characteristics of the optimal scheduling. Specifically, we show that it is crucial to distribute pieces from the server indirectly to peers with large upload capacity via those with small upload capacity.