Chi-Jen Wu

Improving the Download Time of BitTorrent-Like Systems

The content distribution techniques have recently started embracing peer-to-peer system as an alternative to the client-server architecture, such as BitTorrent system. BitTorrent system offers a scale mechanism for distributing a large volume of data to a set of peers over the Internet, but it is not designed for minimizing the time taken for all peers to receive the file. As a result, the peers of BitTorrent system may suffer a long download time, specifically the narrow-band peers. In this paper, in order to reduce the download time of BitTorrent, we propose a weighty piece selection strategy instead of the local rarest first strategy in BitTorrent. The proposed strategy is based on the greedy concept that a peer assigns each missing piece a weight according to total number of neighbors downloaded pieces. The peer selects the missing piece with the highest priority for next download. This strategy can speed up the cooperation between heterogeneous peers while making the BitTorrent more efficient in terms of the average download time and the total elapsed time. The simulation results show that weighty piece selection strategy can improve more than 15% average download time and reduce in average 60% total elapsed time than the BitTorrent system.

A novel efficient power-saving MAC protocol for multi-hop MANETs

Following recent advances in the performance of ad hoc networks, the limited life of batteries in mobile devices poses a bottleneck in their development. Consequently, how to minimize power consumption in the Medium Access Control (MAC) layer of ad hoc networks is an essential issue. The power-saving mode (PSM) of IEEE 802.11 involves the Timing Synchronization Function to reduce power consumption for single-hop mobile ad hoc networks (MANETs). However, the IEEE 802.11 PSM is known to result in unnecessary energy consumption as well as the problems of overheating and back-off time delay. Hence, this study presents an efficient power-saving MAC protocol, called p-MANET, based on a Multi-hop Time Synchronization Protocol, which involves a hibernation mechanism, a beacon inhibition mechanism, and a low-latency next-hop selection mechanism for general-purpose multi-hop MANETs. The main purposes of the p-MANET protocol are to reduce significantly the power consumption and the transmission latency. In the hibernation mechanism, each p-MANET node needs only to wake up during one out of every N beacon interval, where N is the number of beacon intervals in a cycle. Thus, efficient power consumption is achieved. Furthermore, a beacon inhibition mechanism is proposed to prevent the beacon storm problem that is caused by synchronization and neighbor discovery messages. Finally, the low-latency next-hop selection mechanism is designed to yield low transmission latency. Each p-MANET node is aware of the active beacon intervals of its neighbors by using a hash function, such that it can easily forward packets to a neighbor in active mode or with the least remaining time to wake up. As a consequence, upper-layer routing protocols can cooperate with p-MANET to select the next-hop neighbor with the best forwarding delay. To verify the proposed design and demonstrate the favorable performance of the proposed p-MANET, we present the theoretical analysis related to p-MANET and also perform experimental simulations. The numerical results show that p-MANET reduces power consumption and routing latency and performs well in extending lifetime with a small neighbor discovery time. Copyright

A Scalable Server Architecture for Mobile Presence Services in Social Network Applications

Social network applications are becoming increasingly popular on mobile devices. A mobile presence service is an essential component of a social network application because it maintains each mobile users presence information, such as the current status (online/offline), GPS location and network address, and also updates the users online friends with the information continually. If presence updates occur frequently, the enormous number of messages distributed by presence servers may lead to a scalability problem in a large-scale mobile presence service. To address the problem, we propose an efficient and scalable server architecture, called PresenceCloud, which enables mobile presence services to support large-scale social network applications. When a mobile user joins a network, PresenceCloud searches for the presence of his/her friends and notifies them of his/her arrival. PresenceCloud organizes presence servers into a quorum-based server-to-server architecture for efficient presence searching. It also leverages a directed search algorithm and a one-hop caching strategy to achieve small constant search latency. We analyze the performance of PresenceCloud in terms of the search cost and search satisfaction level. The search cost is defined as the total number of messages generated by the presence server when a user arrives; and search satisfaction level is defined as the time it takes to search for the arriving users friend list. The results of simulations demonstrate that PresenceCloud achieves performance gains in the search cost without compromising search satisfaction.

p-MANET: Efficient Power Saving Protocol for Multi-Hop Mobile Ad Hoc Networks

In this paper, we propose an efficient power saving protocol for multi-hop mobile ad hoc networks, called p-MANET. Our design is expected as a new foundation MAC layer power saving protocol. The main goals of p-MANET protocol are to reduce significant power consumption and transmission latency, and to achieve efficient power saving. Each mobile node in p-MANET only needs to become active during one beacon interval for every n interval where n is the size of a super frame. Thus, efficient power saving is expected. p-MANET also yields low transmission latency because that every mobile node is aware of the active beacon intervals of its neighbors such that it can easily choose a neighbor in active mode or with the least remaining time to wake up to forward packets. Simulations are also conducted to show the efficiency of the proposed p-MANET

Time-critical event dissemination in geographically distributed clouds

Cloud computing has rapidly become a new infrastructure for organizations to reduce their capital cost in IT investment and to develop planetary-scale distributed applications. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting intercloud data management and dissemination. In this paper, we present Plume, a generic distributed intercloud overlay for time-critical event dissemination services. Plume aims at improving the interoperability of interclouds in time-critical event dissemination services, such as computing policy updating, message sharing, event notifications and so forth. Plume organizes these distributed clouds into a novel quorum ring overlay to support a constant event dissemination latency. Our numerical results show that the proposed Plume greatly improves the efficiency as compared to a DHT-based overlay approach and provides better scalability than the fully-meshed approach.

A scalable overlay framework for internet anycasting service

This study presents IAS, a scalable and efficient global overlay routing framework for Internet Anycasting Service. We introduce a new routing group concept and adopt the overlay network mechanism to achieve scalable and efficient inter-domain anycast routing. We show that the routing table size of an anycast router can be bounded by O(√N), where N denotes the number of anycast groups. We conduct simulations on a AS topology to verify this bound and show that routes found by IAS are very close to the shortest path when the size of anycast group is reasonably large.

A Novel Pipeline Approach for Efficient Big Data Broadcasting

Big-data computing is a new critical challenge for the ICT industry. Engineers and researchers are dealing with data sets of petabyte scale in the cloud computing paradigm. Thus, the demand for building a service stack to distribute, manage, and process massive data sets has risen drastically. In this paper, we investigate the Big Data Broadcasting problem for a single source node to broadcast a big chunk of data to a set of nodes with the objective of minimizing the maximum completion time. These nodes may locate in the same datacenter or across geo-distributed datacenters. This problem is one of the fundamental problems in distributed computing and is known to be NP-hard in heterogeneous environments. We model the Big-data broadcasting problem into a LockStep Broadcast Tree (LSBT) problem. The main idea of the LSBT model is to define a basic unit of upload bandwidth, r, such that a node with capacity c broadcasts data to a set of [c/r] children at the rater. Note that r is a parameter to be optimized as part of the LSBT problem. We further divide the broadcast data into m chunks. These data chunks can then be broadcast down the LSBT in a pipeline manner. In a homogeneous network environment in which each node has the same upload capacity c, we show that the optimal uplink rate r* of LSBT is either c/2 or c/3, whichever gives the smaller maximum completion time. For heterogeneous environments, we present an O(nlog2n) algorithm to select an optimal uplink rater* and to construct an optimal LSBT. Numerical results show that our approach performs well with less maximum completion time and lower computational complexity than other efficient solutions in literature.

Using Web-Mining for Academic Measurement and Scholar Recommendation in Expert Finding System

Scholars usually spend great deal of time on searching and reading papers of key researchers. However, to objectively determine key researcher of a topic relies on several measurements, such as publication, citation, recent academic activities. In this paper, a prototype of scholars searching and recommendation system based on a web mining approach in expert finding system is proposed. The system gives and recommends the ranking of scholars and turns out top-k scholars. A new ranking measure is designed, namely p-index, to reveal the scholar ranking of a certain field. We use a real-world dataset to test the robustness, the experiment results show our approach outperforms other existing approaches and users are highly interested in using the system again.

A location-aware peer-to-peer overlay network

This work describes a novel location-aware, self-organizing, fault-tolerant peer-to-peer (P2P) overlay network, referred to as Laptop. Network locality-aware considerations are a very important metric for designing a P2P overlay network. Several network proximity schemes have been proposed to enhance the routing efficiency of existing DHT-based overlay networks. However, these schemes have some drawbacks such as high overlay network and routing table maintenance overhead, or not being completely self-organizing. As a result, they may result in poor scalability as the number of nodes in the system grows. Laptop constructs a location-aware overlay network without pre-determined landmarks and adopts a routing cache scheme to avoid maintaining the routing table periodically. In addition, Laptop significantly reduces the overlay maintenance overhead by making each node maintain only the connectivity between parent and itself. Mathematical analysis and simulations are conducted to evaluate the efficiency, scalability, and robustness of Laptop. Our mathematical analysis shows that the routing path length is bounded by logdN, and the joining and leaving overhead is bounded by d logdN, where N is the number of nodes in the system, and d is the maximum degree of each node on the overlay tree. Our simulation results show that the average latency stretch is 1.6 and the average routing path length is only about three in 10 000 Laptop nodes, and the maximum degree of a node is bounded by 32. Copyright

Time-Critical Data Dissemination in Cooperative Peer-to-Peer Systems

How to rapidly disseminate a large-sized file to many recipients is a fundamental problem in many applications, such as updating software patches and distributing large scientific data sets. In this paper, we present the Bee protocol, which is a cooperative peer-to-peer data dissemination protocol aiming at minimizing the maximum dissemination time for all peers to obtain time-critical data, such as critical patch updates. Bee is a decentralized protocol that organizes peers into a randomized mesh-based overlay and each peer only works with local knowledge. We devise a slowest peer first strategy to boost the speed of dissemination, and a topology adaptation algorithm that provides the most efficient utilization of the network capacity. Bee is designed to support network heterogeneity and deal with the flash crowd arrival pattern without sacrificing the dissemination speed. We present experimental results on the performance of Bee in terms of dissemination time and show that its performance can approach lower bound of the maximum dissemination time.