Requested Data Items Research Articles

Coding-Based Data Broadcast Scheduling in On-Demand Broadcast

According to data broadcast, we can satisfy multiple requests for the same data item in a broadcast tick. However, there is no significant breakthrough in performance improvement until recently that some studies proposed to use network coding in data broadcast. After broadcasting an encoded packet which encodes a number of data items, multiple clients can retrieve different requested data items in a broadcast tick. This not only utilizes bandwidth more efficiently, but also improves system performance. In this work, we propose a generalized encoding framework to incorporate network coding into data scheduling algorithms for on-demand broadcast. In the framework, data scheduling can be formulated as a weighted maximum clique problem in a graph where the weight of the clique is defined according to the performance objectives of the applications. Under the proposed framework, existing data scheduling algorithms for on-demand broadcast can be migrated into their corresponding coding versions while preserving their original criteria in scheduling data items. Our simulation results using a number of representative scheduling algorithms show that significant performance improvement can be achieved with coding.

Improving data availability via an economic lease model in mobile-P2P networks

This work proposes LEASE, a novel mobile-P2P lease-based economic incentive model, in which data requestors need to pay the price (in virtual currency) of their requested data items to data-providers. In LEASE, data-providing mobile peers lease data items to other mobile peers in lieu of a lease payment. The main contributions of LEASE are three-fold. First, its lease model entices even those users, who have no data to provide, to host data items, thereby improving data availability and MP revenues. Second, its economic model discourages free-riding, which improves connectivity due to higher peer participation. Third, its Vickrey auction-based bidding mechanism for leasing items provides effective leasing incentives to peers for improving data availability. Our performance study shows that LEASE indeed improves query response times and data availability in mobile-P2P networks.

Exploiting In-Zone Broadcasts for Cache Sharing in Mobile Ad Hoc Networks

The problem of cache sharing for supporting data access in mobile ad hoc networks is studied in this paper. The key to this problem is to discover a requested data item in an efficient manner. In the paper, we propose two caching protocols, IXP and DPIP, which distinguish themselves from the existing ones in that they fully exploit in-zone broadcasts to facilitate cache sharing operation. In particular, the DPIP protocol offers an implicit index push property, which is highly useful for enhancing cache hit ratio in the neighborhood of a data requester node. Moreover, our protocols also exploit the broadcasts to facilitate the design of a simple but efficient count-based cache replacement scheme. Performance study shows that the proposed protocols can significantly improve the performance of data access in a mobile ad hoc network.

AN ANALYSIS OF PROCEDURES AND OBJECTIVE FUNCTIONS FOR HEURISTICS TO PERFORM DATA STAGING IN DISTRIBUTED SYSTEMS

The data staging problem involves positioning data within a distributed heterogeneous computing environment such that programs can access the requested data faster. This problem exists because applications constantly need up-to-date information to enable users to make decisions. In addition, these requests for information are normally occurring in an oversubscribed network. In such a heterogeneous distributed computing environment, each data storage location and intermediate node may have different data available, storage limitations, and communication links available. Sites in the heterogeneous network request data items and each request has an associated deadline and priority. This work extends the research presented in [ThT00] where a basic version of the data staging problem with static information was presented. This work introduces three new cost criteria and two new bounds on performance that were designed taking into account results from [ThT00]. A subset of the possible procedure/cost criterion combinations are evaluated in simulation studies considering a different priority weighting scheme, different average number of links used to satisfy each data request, and different network loadings, than was considered in [ThT00]. This paper also introduces a variable time, variable accuracy approach for using data items with "more desirable" and "less desirable" versions.

Scheduling Strategies Of Correlated Broadcast Data In Push-Based Systems

The server strategy of repeatedly broadcasting data items can result in a higher throughput than sending the requested data items to individual clients. Various methods have been studied to reduce the average response time in such systems. In this paper, two strategies are presented for scheduling the broadcast program. Both strategies take into account the correlation among the requested data items. The first strategy is suitable for an environment where clients access a set of correlated data items by submitting multiple access requests at the same time. A broadcast program is composed by placing strongly correlated data items next to each other. The second strategy is suitable for an environment where clients access a set of correlated data items by submitting multiple access requests at intervals between the requests. This latter strategy places strongly correlated data items at suitable intervals in the program. Simulation studies were used to evaluate the performance of the proposed strategies.

A mathematical model and scheduling heuristics for satisfying prioritized data requests in an oversubscribed communication network

Providing up-to-date input to users' applications is an important data management problem for a distributed computing environment, where each data storage location and intermediate node may have specific data available, storage limitations, and communication links available. Sites in the network request data items and each request has an associated deadline and priority. In a military situation, the data staging problem involves positioning data for facilitating a faster access time when it is needed by programs that will aid in decision making. This work concentrates on solving a basic version of the data staging problem in which all parameter values for the communication system and the data request information represent the best known information collected so far and stay fixed throughout the scheduling process. The network is assumed to be oversubscribed and not all requests for data items can be satisfied. A mathematical model for the basic data staging problem is introduced. Then, three multiple-source shortest-path algorithm-based heuristics for finding a near-optimal schedule of the communication steps for staging the data are presented. Each heuristic can be used with each of four cost criteria developed. Thus, 12 implementations are examined. In addition, two different weightings for the relative importance of different priority levels are considered. The performance of the proposed heuristics are evaluated and compared by simulations. The proposed heuristics are shown to perform well with respect to upper and lower bounds. Furthermore, the heuristics and a complex cost criterion allow more highest priority messages to be received than a simple-cost-based heuristic that schedules all highest priority messages first.