Wireless Data Broadcast Research Articles

NN Search based on Non-uniform Space Partition on Air

It is one of most important challenges in information services based on location to support a huge number of clients to process the NN query for a given query point. A scheme of NN query processing based on wireless data broadcasting is an effective way to overcome the challenge. In this paper, we propose an indexing scheme NSPI (Non-uniform Space Partition Index) for quick NN search over wireless data broadcasting. For implementing the aim, we use a non-uniform spatial partition and provide an index based on the partition for equidistance between indexes on the wireless channel. The index scheme enables the clients to process NN quickly by lessening the time for the clients to meet the index on the channel. To show the effectiveness of the proposed scheme, we compare the access time and tuning time of the clients with existing indexing schemes by simulation studies. The proposed NSPI shows shorter access time than the other existing scheme. Also, NSPI outperforms in the aspect of tuning time than the others.

DZI: An air index for spatial queries in one-dimensional channels

The wireless data broadcast environment characteristics cause the data to be delivered sequentially via one-dimensional channels. A space-filling curve has been proposed for recent wireless data broadcast environments. However, air indexing introduces various problems, including the increase in the size of the index, conversion costs, and an increase in the search space because of an inefficient structure. In this paper, we propose a distribution-based Z-order air index and query processing algorithms suitable for a wireless data broadcast environment. The proposed index organizes the object identification (hereafter called ID) hierarchically only in terms of objects that are present. We compare the proposed technique with the well-known spatial indexing technique DSI by creating equations that represent the access time and tuning time, followed by conducting a simulation-based performance evaluation. The results from experimental show that our proposed index and algorithms support efficient query processing in both range queries and K-nearest neighbor queries.

Online algorithm for data retrieval with multiple antennae in wireless communication

Given a set of requested data items and a set of multiple channels, online multi-antennae data retrieval problem (OMAP) is to download all requested data items from these channels when the clients are equipped with multiple antennae and do not know any a-prior knowledge of wireless data broadcast system, such that the total access latency is minimised and the access latency among all antennae keeps balance. So this paper proposes online multiple antennae data retrieval algorithm based on requested ratio (OMR) and online multiple antennae retrieval algorithm for equal data items based on unretrieved ratio (OMU) that introduces the requested ratio and unretrieved ratio respectively when the length of data items is equal. In addition, when the length of data items is unequal, the paper proposes online multiple antennae retrieval algorithm for unequal data items based on length ratio (OML) that introduces the length to compute the length ratio. Finally, we analyse the competitive rates of three algorithms. Through experiments, the proposed schemes can have currently better efficiency by comparing with some existing schemes and solve OMAP.

Online algorithm for data retrieval with multiple antennae in wireless communication

Given a set of requested data items and a set of multiple channels, online multi-antennae data retrieval problem (OMAP) is to download all requested data items from these channels when the clients are equipped with multiple antennae and do not know any a-prior knowledge of wireless data broadcast system, such that the total access latency is minimised and the access latency among all antennae keeps balance. So this paper proposes online multiple antennae data retrieval algorithm based on requested ratio (OMR) and online multiple antennae retrieval algorithm for equal data items based on unretrieved ratio (OMU) that introduces the requested ratio and unretrieved ratio respectively when the length of data items is equal. In addition, when the length of data items is unequal, the paper proposes online multiple antennae retrieval algorithm for unequal data items based on length ratio (OML) that introduces the length to compute the length ratio. Finally, we analyse the competitive rates of three algorithms. Through experiments, the proposed schemes can have currently better efficiency by comparing with some existing schemes and solve OMAP.

Efficient algorithm for online data retrieval with one antenna in wireless networks

Given a set of requested data items and a set of multiple channels, data retrieval problem is to find a data retrieval sequence for downloading all requested data items from these channels in a reasonable time range. Almost all existing schemes are applied in offline environment that the client can learn prior knowledge of wireless data broadcast, such as the set of broadcast channels and the broadcast time of data items. However, this information is unknown in online data retrieval. So this paper proposes three online algorithms (MRLR, RM and MRM) for solving online data retrieval problem. Compared with the optimal offline data retrieval algorithm, MRLR, RM and MRM algorithms hold (k ‒ 1), (log(k ‒ 1) + k/2 ) and k/2 competitive rate respectively. Through comparison with the competitive rates and experimental results of proposed online algorithms, we observe that the performance of online data retrieval is improved in wireless networks.

RPPM: A Request Pre-Processing Method for Real-Time On-Demand Data Broadcast Scheduling

Wireless on-demand data broadcasting (ODDB) has become the preferred method of disseminating data to a large number of mobile users. The rapid boom in client requests has resulted in an urgent demand for improved ODDB system capacity (number of service users), especially in client-intensive and request-frequent environments. There are two bottlenecks in ODDB systems: the base station access capacity and the server concurrency capability. However, existing algorithms do not consider these bottlenecks, leading to deficient performance in ODDB system capacity and broadcast efficiency. In this paper, a three-layer ODDB system architecture and a request pre-processing method (RPPM) are proposed. The innovations of this study are twofold: (1) The three-layer ODDB system architecture enhances the base station access capacity by introducing a virtual node layer to share the high load of the base station. (2) Based on the proposed architecture, the RPPM handles request merger and priority evaluation to reduce server concurrency and improve broadcast efficiency. The results of experiments and analyses reveal that the proposed method can significantly enhance the ODDB system capacity and obtain outstanding broadcast efficiency.

Energy-Efficient Data Access Using Spatial Index in the Wireless Data Broadcast for Location-Dependent Healthcare Services

Energy-Efficient Data Access Using Spatial Index in the Wireless Data Broadcast for Location-Dependent Healthcare Services

Efficient Approximation Algorithms for Multi-Antennae Largest Weight Data Retrieval

In a mobile network, wireless data broadcast over $m$ channels (frequencies) is a powerful means for distributed dissemination of data to clients who access the channels through multi-antennae equipped on their mobile devices. The $\delta$-antennae largest weight data retrieval ($\delta$ALWDR) problem is to compute a schedule for downloading a subset of data items that has a maximum total weight using $\delta$ antennae in a given time interval. In this paper, we propose a ratio $1-\frac{1}{e}-\epsilon$ approximation algorithm for the $\delta$-antennae largest weight data retrieval ($\delta$ALWDR) problem that has the same ratio as the known result but a significantly improved time complexity of $O(2^{\frac{1}{\epsilon}}\frac{1}{\epsilon}m^{7}T^{3.5}L)$ from $O(\epsilon^{3.5}m^{\frac{3.5}{\epsilon}}T^{3.5}L)$ when $\delta=1$ \cite{lu2014data}. To our knowledge, our algorithm represents the first ratio $1-\frac{1}{e}-\epsilon$ approximation solution to $\delta$ALWDR for the general case of arbitrary $\delta$. To achieve this, we first give a ratio $1-\frac{1}{e}$ algorithm for the $\gamma$-separated $\delta$ALWDR ($\delta$A$\gamma$LWDR) with runtime $O(m^{7}T^{3.5}L)$, under the assumption that every data item appears at most once in each segment of $\delta$A$\gamma$LWDR, for any input of maximum length $L$ on $m$ channels in $T$ time slots. Then, we show that we can retain the same ratio for $\delta$A$\gamma$LWDR without this assumption at the cost of increased time complexity to $O(2^{\gamma}m^{7}T^{3.5}L)$. This result immediately yields an approximation solution of same ratio and time complexity for $\delta$ALWDR, presenting a significant improvement of the known time complexity of ratio $1-\frac{1}{e}-\epsilon$ approximation to the problem.

Organizing XML Data in a Wireless Broadcast System by Exploiting Structural Similarity

Wireless data broadcast is an efficient way of delivering data of common interest to a large population of mobile devices within a proximate area, such as smart cities, battle fields, etc. In this work, we focus ourselves on studying the data placement problem of periodic XML data broadcast in mobile and wireless environments. This is an important issue, particularly when XML becomes prevalent in today’s ubiquitous and mobile computing devices and applications. Taking advantage of the structured characteristics of XML data, effective broadcast programs can be generated based on the XML data on the server only. An XML data broadcast system is developed and a theoretical analysis on the XML data placement on a wireless channel is also presented, which forms the basis of the novel data placement algorithm in this work. The proposed algorithm is validated through a set of experiments. The results show that the proposed algorithm can effectively place XML data on air and significantly improve the overall access efficiency.

Dynamic priority scheduling of periodic queries in on-demand data dissemination systems

As an important wireless data broadcast technique, on-demand broadcast has been widely used for dynamic and large-scale data dissemination. An important class of emerging data broadcast applications requires monitoring multiple data items continuously in order to support data-driven decision making. Since wireless bandwidth is a precious shared medium, an important problem to solve is how to disseminate data to periodic queries, so that all the requests can be satisfied while the bandwidth consumption is minimized. In this paper, we first propose a new real-time scheduling algorithm called EDFS, which is a variant of the classic EDF [24] algorithm. Based on EDFS, we propose a novel on-line broadcast scheduling algorithm, called EDFS-BS. To our best knowledge, EDFS-BS is the first dynamic priority based broadcast scheduling algorithm that can be utilized to satisfy the timing constraints of periodic queries. We also propose a bandwidth utilization based schedulability test for EDFS-BS, which is used to ensure timing predictability of a periodic query set. Extensive experiments have been conducted to compare EDFS-BS versus existing solutions with comparable quality. The results show that EDFS-BS outperforms them considerably in terms of wireless bandwidth consumption and query service ratio.

Editorial for the special issue on heterogeneous sensors–based object identification and information fusion

With the fast development of computing, communication, control technologies, the proliferation of heterogeneous sensors with data communication capability can provide a wide variety of data for our daily life, such as road monitoring, health-care systems, structure health checking, military applications etc. However, there are still many interesting open research problems left to be explored as well as many issues to be addressed. In this special issue, we plan to focus on various research and application issues in heterogeneous sensors based object identification and information fusion. The first paper, 'A novel distributed air index for efficient spatial query processing in road sensor networks on the air' by Yanhong Li et al., explores the problem of spatial query processing in road sensor networks by means of wireless data broadcast. In addition it presents an efficient method to partition the record-keeping information about the underlying road sensor network and its associated objects, by which develops a fully distributed air index, called integrated exponential index, based on an extended version of the Hilbert curve. Besides, this paper also proposes efficient client-side algorithms to facilitate the processing of several kinds of spatial queries, including kNN query, CkNN query, and range query. The problem of enforcing the integrity of the outsourced data remotely is addressed in the paper, 'Parallel checking of content integrity in multi-cloud storage of heterogeneous sensor systems' by Jian Mao et al.. They propose a parallel cloud data possession checking scheme for the multi-cloud environment, which utilizes the homomorphic verification tag created by the Paillier cryptosystem to support unlimited query challenges and introduces the error-correction encoding method to ensure error localization and data correction. The paper, 'Subscribing to fuzzy temporal aggregation of heterogeneous sensor streams in real-time distributed environments' by J. Medina et al., presents an approach for distributing and processing heterogeneous data based on a representation with fuzzy linguistic terms, to solve the problems of the data fusion of sensors and the design of processing information. What's more, in order to illustrate the usefulness and effectiveness of this proposal, the authors present the results of the fuzzy temporal aggregation of sensor streams with alpha-cut subscriptions in a case study where an

Spatial query processing for skewed access patterns in nonuniform wireless data broadcast environments

Location-based services (LBSs) via wireless data broadcast can provide a huge number of mobile clients for simultaneously accessing spatial data according to their current locations. Under non-uniform wireless data broadcast, more popular data appear more times than regular data, resulting in the decrease of the average client waiting time. In this paper, to efficiently support the processing of continuous window queries for LBSs, we propose a skewed spatial index considering clients' skewed access patterns in the non-uniform wireless broadcast environments. The index information considering the non-uniform broadcast is interleaved with the spatial objects on the wireless channel to support efficient access. From our experimental study, we have shown that our proposed method outperforms the multi-levelled air index scheme.

Quick Window Query Processing Using a Non-Uniform Cell-Based Index in Wireless Data Broadcast Environment

Quick Window Query Processing Using a Non-Uniform Cell-Based Index in Wireless Data Broadcast Environment

Spatial query processing for skewed access patterns in non-uniform wireless data broadcast environments

Spatial query processing for skewed access patterns in non-uniform wireless data broadcast environments

Dict-Based Energy and Latency Efficient Air Indexing Technique for Full Text Search Over Wireless Broadcast Stream

Wireless data broadcasting seems to be an efficient way for dissemination of data to a large number of mobile users. Because of its scalability and flexibility, the service providers use this technology to resolve request of thousands of users in one single response. Full text search is the latest area of research in wireless data broadcasting. Access time and tuning time are the two metrics for evaluation of an indexing technique. In this paper, we propose an air indexing technique based on the dictionary data structure namely Dict-Based Air Indexing Technique for full text search over wireless broadcast stream that utilizes hash-tables. We also propose algorithms for the implementation of the technique. We analyze, evaluate and compare its performance with existing schemes. The results from simulation experiments demonstrate that the proposed technique is the most latency and energy efficient air indexing technique for full text searches.

Global Optimization for Multi-Channel Wireless Data Broadcast with AH-Tree Indexing Scheme

Multi-channel wireless data broadcast is an appropriate approach to disseminate data to a mass number of mobile clients. In this paper, we present a global optimization for multi-channel wireless data broadcast with Alphabetic Huffman Tree (AH-Tree) Indexing scheme, which can deal with skewed access frequencies well. We present three novel designs to reduce the access latency and tuning time of the broadcast system. Firstly, we design a dynamic programming for AH-Tree construction with low time complexity. Compared with traditional Hu-Tucker algorithm in $O(n^k)$ , our algorithm can build a $k$ -ary AH-Tree index in $O(n^2)$ . Next, we depict a new control table design, which eliminates up to 50 percent redundant entries while keeps the searching efficiency. We also theoretically prove that an optimal alphabetic tree has the minimum average tuning time among all tree-based index structures for skewed data broadcast. Thirdly, we design the new index and data allocation algorithms to further reduce the tuning time and access latency. The simulation results validate the effectiveness of our algorithms. In all, our global optimization mechanism can greatly improve the system performance and time efficiency for wireless data broadcast applications.

A Real-time scheduling algorithm for on-demand wireless XML data broadcasting

Extensive Markup Language (XML) has been widely used to exchange and storage mass data in mobile computing environment. The existing research focuses on preprocessing XML document and index building, but there are little research relating to how to arrange the scheduling contents and the broadcasting sequence. This paper puts forward a real-time scheduling algorithm for on-demand wireless XML data broadcasting – XML-RxW/L to reduce the request drop ratio, average accessing time and average tuning time. Our work can be divided into the three parts: (1) XML-RxW/L is proposed to reduce the request drop ratio and average accessing time. (2) An index strategy is proposed to reduce the average tuning time by forecasting data item queue. A dynamic adjusting method on the index cycle length of XML wireless data broadcasting (X_DAIL) is proposed to determine the proper index cycle dynamically. (3) A pruning algorithm (X_Prune) of XML document is proposed to remove redundant information of XML documents. An index-building algorithm (X_Index) is proposed based on DataGuide index structure to upgrade the response speed and the accuracy rate of query request. Extensive experimental results show that the XML-RxW/L algorithm has better performance than other state-of-the-art scheduling algorithms on a real data set and a synthetic data set. A real case study by R3 system shows that the proposed algorithm presents an improvement at almost 10% than other comparable algorithms in request drop ratio (RDR), smaller at almost 6–10 s in average accessing time (AAT); and smaller at almost 12s in average tuning time (ATT).

A novel distributed air index for efficient spatial query processing in road sensor networks on the air

SummaryRecent development of wireless technology and smart mobile devices has spurred intense research efforts to address spatial queries. In particular, an increasing interest for tackling spatial query processing in broadcast environments has been observed. To the best of our knowledge, most of the existing work on this problem has assumed an Euclidean space. However, for real applications, query clients move within a road sensor network, where the distance between a data object and a query is determined by the connectivity of the road sensor network. This paper explores the problem of spatial query processing in road sensor networks by means of wireless data broadcast. We present an efficient method to partition the record‐keeping information about the underlying road sensor network and its associated objects, by which we develop a fully distributed air index, called integrated exponential index, based on an extended version of the Hilbert curve. We also propose efficient client‐side algorithms to facilitate the processing of several kinds of spatial queries, including kNN query, CkNN query, and range query. Finally, extensive simulation experiments have been conducted to demonstrate the strengths of our proposed techniques. Copyright © 2016 John Wiley & Sons, Ltd.

XML 기반 CCR 문서의 무선 데이터 방송을 위한 프레임워크의 설계와 구현

In the field of health informatics converging ICT technology and medicine technology, XML-based CCR document make sure the continuity and mobility of the information of patients. When a number of clients access CCR documents, wireless data broadcast that supports any number of clients can be an alternative for the scalability. In this paper, we propose a framework for wireless data broadcast of XML-based CCR documents. We design and implement the framework that can adopt various data scheduling algorithms and indexing schemes for the optimized performances of clients. The implemented framework shows the efficiency with simulations adopting various data scheduling algorithms and indexing schemes.

Heuristic Algorithm for Efficient Data Retrieval Scheduling in the Multichannel Wireless Broadcast Environments

Wireless data broadcast is an efficient way of disseminating data to users in the mobile computing environments. From the server’s point of view, how to place the data items on channels is a crucial issue, with the objective of minimizing the average access time and tuning time. Similarly, how to schedule the data retrieval process for a given request at the client side such that all the requested items can be downloaded in a short time is also an important problem. In this paper, we investigate the multi-item data retrieval scheduling in the push-based multichannel broadcast environments. The most important issues in mobile computing are energy efficiency and query response efficiency. However, in data broadcast the objectives of reducing access latency and energy cost can be contradictive to each other. Consequently, we define a new problem named Minimum Cost Data Retrieval Problem (MCDR) and Large Number Data Retrieval (LNDR) Problem. We also develop a heuristic algorithm to download a large number of items efficiently. When there is no replicated item in a broadcast cycle, we show that an optimal retrieval schedule can be obtained in polynomial time.