Data broadcasting for dependent information using multiple channels in wireless broadcast environments

Data broadcasting is an effective approach to disseminating information to mobile clients and has attracted much research attention in recent years. In many applications, the access pattern among the data can be represented by a weighted DAG. In this paper, we consider the problem of efficiently generating the broadcast schedules on multiple channels when the data set has a DAG access pattern. We show that it is NP-hard to find an optimal broadcast schedule which not only minimizes the latency but also satisfies the ancestor property that retains the data dependency. We further derive a condition for the input DAGs under which one can generate an optimal broadcast schedule in linear time and propose an algorithm to generate the schedule. Due to the NP-completeness, we provide three heuristics for general DAGs based on the level of a vertex in the input DAGs and each heuristic uses a different policy to place vertices into the broadcast channels. There are two categories for the policies. The first category mainly considers the probability for a process to stop at a considered vertex. The second category takes the vertices which are affected most when assigning a vertex into consideration. We analyze and discuss these heuristics. A short experimental simulation is given for supporting and validating the discussion. In particular, the experimental results indicate that roughly considering the whole posterior vertices of each vertex is not precise and may not lead to good results and considering the vertices affected most when assigning a vertex will help reducing the latency.     

Efficient XML data placement schemes over multiple mobile wireless broadcast channels

The Journal of Supercomputing - Broadcasting is one of the basic ways to access XML data via mobile wireless networks. In these networks, XML data are disseminated over a wireless broadcast channel...     

An efficient nonuniform index in the wireless broadcast environments

Data broadcast is an efficient dissemination method to deliver information to mobile clients through the wireless channel. It allows a huge number of the mobile clients simultaneously access data in the wireless environments. In real-life applications, more popular data may be frequently accessed by clients than less popular ones. Under such scenarios, Acharya et al.’s Broadcast Disks algorithm (BD) allocates more popular data appeared more times in a broadcast period than less popular ones, i.e., the nonuniform broadcast, and provides a good performance on reducing client waiting time. However, mobile devices should constantly tune in to the wireless broadcast channel to examine data, consuming a lot of energy. Using index technologies on the broadcast file can reduce a lot of energy consumption of the mobile devices without significantly increasing client waiting time. In this paper, we propose an efficient nonuniform index called the skewed index, SI, over BD. The proposed algorithm builds an index tree according to skewed access patterns of clients, and allocates index nodes for the popular data more times than those for the less popular ones in a broadcast cycle. From our experimental study, we have shown that our proposed algorithm outperforms the flexible index and the flexible distributed index.     

多信道无线通信功率分配的最优化决策

研究了基于有损Gilbert-Elliott信道的多信道无线通信功率分配的最优化决策问题,利用部分可观测的马尔可夫决策过程（POMDP）和数学语言建立并描述理论模型,提出了具有一般性的功率分配方案,并给出问题的最优决策的各项性质和特征。在三维信道的通信系统上,进一步给出最优决策的空间结构,利用线性规划仿真验证了其正确性,并分析了最优决策随信道转移概率的变化趋势。     

Disseminating dependent data in wireless broadcast environments

In wireless mobile environments, data broadcasting is an effective approach to disseminate information to mobile clients. In some applications, the access pattern of all the data can be represented by a weighted DAG. In this paper, we explore how to efficiently generate the broadcast schedule in a wireless environment for the data set having a weighted DAG access pattern. Such a broadcast schedule not only minimizes the access latency but also is a topological ordering of the DAG. Minimized access latency ensures the quality of service (QoS). We prove that it is NP-hard to find an optimal broadcast schedule and provide some heuristics. After giving an analysis for these heuristics on the latency and complexity, we implement all the proposed heuristics to compare their performance. Recommended by: Sunil Prabhakar     

Web caching in broadcast mobile wireless environments

Effectively exploiting available communication bandwidth and client resources is vital in wireless mobile environments. One technique for doing so is client-side data caching, which helps reduce latency and conserve network resources. The SliCache generic self-tunable cache-replacement policy addresses these issues by using intelligent slicing of the cache space and novel methods for selecting which objects to purge. Performance evaluations show that SliCache improves mobile clients' access to Web objects compared to other common policies.     

An energy-efficient mobile transaction processing method using random back-off in wireless broadcast environments

Broadcast is widely accepted as an efficient technique for disseminating data to a large number of mobile clients over a single or multiple channels. Due to the limited uplink bandwidth from mobile clients to server, conventional concurrency control methods cannot be directly applied. There has been many researches on concurrency control methods for wireless broadcast environments. However, they are mostly for read-only transactions or do not consider exploiting cache. They also suffer from the repetitive aborts and restarts of mobile transactions when the access patterns of mobile transactions are skewed. In this paper, we propose a new optimistic concurrency control method suitable for mobile broadcast environments. To prevent the repetitive aborts and restarts of mobile transactions, we propose a random back-off technique. To exploit the cache on mobile clients, our method keeps the read data set of mobile transactions and prefetches those data items when the mobile transactions are restarted. As other existing optimistic concurrency control methods for mobile broadcast environments does, it works for both read-only and update transactions. Read-only transactions are validated and locally committed without using any uplink bandwidth. Update transactions are validated with forward and backward validation, and committed after final validation consuming a small amount of uplink bandwidth. Our performance analysis shows that it significantly decreases uplink and downlink bandwidth usage compared to other existing methods.     

A distributed spatial index for error-prone wireless data broadcast

Information is valuable to users when it is available not only at the right time but also at the right place. To support efficient location-based data access in wireless data broadcast systems, a distributed spatial index (called DSI) is presented in this paper. DSI is highly efficient because it has a linear yet fully distributed structure that naturally shares links in different search paths. DSI is very resilient to the error-prone wireless communication environment because interrupted search operations based on DSI can be resumed easily. It supports search algorithms for classical location-based queries such as window queries and kNN queries in both of the snapshot and continuous query modes. In-depth analysis and simulation-based evaluation have been conducted. The results show that DSI significantly out-performs a variant of R-trees tailored for wireless data broadcast environments.     

故障样本的多指标集成加权分配方法

针对测试性验证实验中故障样本分配结果置信度比较低的问题,提出了一种多指标集成加权的分配方法。首先,综合分析故障属性与环境因子对故障样本分配结果置信度的影响,在此基础上,定量计算影响指标的值;其次,采用集成加权法确定各个指标的权重;最后,利用归一化后的指标比值进行故障样本分配。该方法改进了故障率、严酷度、危害度及指标权重的计算方法,并提出了故障样本分配中故障-环境关联度的计算方法。在某型装备故障样本分配中的应用结果表明,该方法的分配结果更合理,置信度更高,更具有实际应用价值。     

Effects of broadcast errors on concurrency control in wireless broadcasting environments

In wireless broadcasting environments, mobile clients cannot receive data reliably over broadcast channels because a reliable transmission protocol is not applicable to the channels. If such broadcast errors are not properly handled by a concurrency control algorithm, it could lead to a fatal effect especially when clients are permitted to issue update transactions. However, the effects of broadcast errors on concurrency control have been little researched. In this paper, we have proposed a concurrency control algorithm to support update transactions issued by mobile clients and evaluated the performance of the algorithm by focusing the effects of broadcast errors with an analytic model. The analytic results show our algorithm is efficient in resolving the broadcast errors.     

Throughput analysis in wireless networks with multiple users and multiple channels

We consider the problem of maximizing throughput in a multi-carrier wireless network that employs predictive link adaptation. We explicitly consider the time-penalty incurred due to link adaptation. The contributions of this paper are twofold. Firstly, several high performance algorithms (offline and online) are developed for efficient performance in multiple user and multiple channel environment under the practicable lookahead prediction of one time slot. Secondly, the presented algorithms and heuristics are shown to be competitive by deterministic and probabilistic analyses. Our results show that a modest consumption of resources for channel prediction and link adaptation may result in a significant throughput improvement.     

A hybrid scheduling scheme for data broadcast over a single channel in mobile environments

Various broadcast schemes have been proposed to reduce the data access time of mobile clients. However, they are based either on the mobile users’ data access frequencies or on the semantic relations of the data. In this paper, we present a hybrid data broadcast scheme based both on semantic relationships and access probabilities. The broadcast scheme we propose generates a broadcast sequence according to the semantic relationships and replicates popular data items several times according to the data access probabilities. The efficiency of our broadcast scheme is shown via performance evaluations.     

Trustworthy-based efficient data broadcast model for P2P interaction in resource-constrained wireless environments

In a decentralised system like P2P where each individual peers are considerably autonomous, the notion of mutual trust between peers is critical. In addition, when the environment is subject to inherent resource constraints, any efficiency efforts are essentially needed. In light of these two issues, we propose a novel trustworthy-based efficient broadcast scheme in a resource-constrained P2P environment. The trustworthiness is associated with the peer?s reputation. A peer holds a personalised view of reputation towards other peers in four categories namely SpEed, Correctness, qUality, and Risk-freE (SeCuRE). The value of each category constitutes a fraction of the reliability of individual peer. Another factor that contributes to the reliability of a peer is the peer?s credibility concerning trustworthiness in providing recommendation about other peers. Our trust management scheme is applied in conjunction with our trust model in order to detect malicious and collaborative-based malicious peers. Knowledge of trustworthiness among peers is used in our proposed broadcast model named trustworthy-based estafet multi-point relays (TEMPR). This model is designed to minimise the communication overhead between peers while considering the trustworthiness of the peers such that only trustworthy peer may relay messages to other peers. With our approach, each peer is able to disseminate messages in the most efficient and reliable manner.     

Maximum throughput of multiple access channels in adversarial environments

We consider deterministic distributed broadcasting on multiple access channels in the framework of adversarial queuing. Packets are injected dynamically by an adversary that is constrained by the injection rate and the number of packets that may be injected simultaneously; the latter we call burstiness. A protocol is stable when the number of packets in queues at the stations stays bounded. The maximum injection rate that a protocol can handle in a stable manner is called the throughput of the protocol. We consider adversaries of injection rate 1, that is, of one packet per round, to address the question if the maximum throughput 1 can be achieved, and if so then with what quality of service. We develop a protocol that achieves throughput 1 for any number of stations against leaky-bucket adversaries. The protocol has O(n²+\textburstiness){\mathcal{O}(n^2+\text{burstiness})} packets queued simultaneously at any time, where n is the number of stations; this upper bound is proved to be best possible. A protocol is called fair when each packet is eventually broadcast. We show that no protocol can be both stable and fair for a system of at least two stations against leaky-bucket adversaries. We study in detail small systems of exactly two and three stations against window adversaries to exhibit differences in quality of broadcast among classes of protocols. A protocol is said to have fair latency if the waiting time of packets is O(\textburstiness){\mathcal{O}(\text{burstiness})}. For two stations, we show that fair latency can be achieved by a full sensing protocol, while there is no stable acknowledgment based protocol. For three stations, we show that fair latency can be achieved by a general protocol, while no full sensing protocol can be stable. Finally, we show that protocols that either are fair or do not have the queue sizes affect the order of transmissions cannot be stable in systems of at least four stations against window adversaries.     

On Kalman filtering over fading wireless channels with controlled transmission powers

We study stochastic stability of centralized Kalman filtering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.     

Improved classification with allocation method and multiple classifiers

Classification is the most used supervized machine learning method. As each of the many existing classification algorithms can perform poorly on some data, different attempts have arisen to improve the original algorithms by combining them. Some of the best know results are produced by ensemble methods, like bagging or boosting. We developed a new ensemble method called allocation. Allocation method uses the allocator, an algorithm that separates the data instances based on anomaly detection and allocates them to one of the micro classifiers, built with the existing classification algorithms on a subset of training data. The outputs of micro classifiers are then fused together into one final classification. Our goal was to improve the results of original classifiers with this new allocation method and to compare the classification results with existing ensemble methods. The allocation method was tested on 30 benchmark datasets and was used with six well known basic classification algorithms (J48, NaiveBayes, IBk, SMO, OneR and NBTree). The obtained results were compared to those of the basic classifiers as well as other ensemble methods (bagging, MultiBoost and AdaBoost). Results show that our allocation method is superior to basic classifiers and also to tested ensembles in classification accuracy and f-score. The conducted statistical analysis, when all of the used classification algorithms are considered, confirmed that our allocation method performs significantly better both in classification accuracy and f-score. Although the differences are not significant for each of the used basic classifier alone, the allocation method achieved the biggest improvements on all six basic classification algorithms. In this manner, allocation method proved to be a competitive ensemble method for classification that can be used with various classification algorithms and can possibly outperform other ensembles on different types of data.     

An efficient stream structure for broadcasting the encrypted XML data in mobile wireless broadcast channels

In mobile wireless broadcast networks, XML data is encrypted before it is sent over the broadcast channel in order to ensure the confidentiality of XML data. In these networks, mobile clients must not have access to all the XML data; rather they should have access to some parts of the XML data that are relevant to them and to which they are authorized to have access. In this paper, a new encrypted XML data stream structure is proposed which supports the confidentiality of XML data over the broadcast channel. In our proposed stream structure, the size of encrypted XML data stream is reduced by grouping the paths, XML nodes, texts, and attributes together. The proposed structure includes several indexes to skip from irrelevant data over the broadcast channel. The experimental results demonstrate that the use of our proposed stream structure efficiently disseminates XML data in mobile wireless broadcast networks in a secure manner and the indexes in our proposed stream structure improve the performance of XML query processing over the encrypted XML data stream.

     

A topology control approach for utilizing multiple channels in multi-radio wireless mesh networks

We consider the channel assignment problem in a multi-radio wireless mesh network that involves assigning channels to radio interfaces for achieving efficient channel utilization. We present a graph–theoretic formulation of the channel assignment guided by a novel topology control perspective, and show that the resulting optimization problem is NP-complete. We also present an ILP formulation that is used for obtaining a lower bound for the optimum. We then develop a new greedy heuristic channel assignment algorithm (termed CLICA) for finding connected, low interference topologies by utilizing multiple channels. Our evaluations show that the proposed CLICA algorithm exhibits similar behavior and comparable performance relative to the optimum bound with respect to interference and capacity measures. Moreover, our extensive simulation studies show that it can provide a large reduction in interference even with a small number of radios per node, which in turn leads to significant gains in both link layer and multihop performance in 802.11-based multi-radio mesh networks.     

Optimizing index allocation for sequential data broadcasting in wireless mobile computing

Energy saving is one of the most important issues in wireless mobile computing. Among others, one viable approach to achieving energy saving is to use an indexed data organization to broadcast data over wireless channels to mobile units. Using indexed broadcasting, mobile units can be guided to the data of interest efficiently and only need to be actively listening to the broadcasting channel when the relevant information is present. We explore the issue of indexing data with skewed access for sequential broadcasting in wireless mobile computing. We first propose methods to build index trees based on access frequencies of data records. To minimize the average cost of index probes, we consider two cases: one for fixed index fanouts and the other for variant index fanouts, and devise algorithms to construct index trees for both cases. We show that the cost of index probes can be minimized not only by employing an imbalanced index tree that is designed in accordance with data access skew, but also by exploiting variant fanouts for index nodes. Note that, even for the same index tree, different broadcasting orders of data records will lead to different average data access times. To address this issue, we develop an algorithm to determine the optimal order for sequential data broadcasting to minimize the average data access time. Performance evaluation on the algorithms proposed is conducted. Examples and remarks are given to illustrate our results.     

Utility-based scheduling in wireless multi-hop networks over non-deterministic fading channels

In this paper, an innovative scheduling scheme is proposed for interference-limited wireless multi-hop networks with non-deterministic fading channels. The scheduling problem is considered as a network utility maximization (NUM) problem subject to link rate constraints. By jointly taking into account of the link scheduling and the statistical variations of signal and interference power, the convex sets for the NUM are derived. Two types of non-deterministic fading channels (i.e., Rayleigh fading channel and Ricean fading channel) are characterized into our NUM models as examples. To solve the convex optimization problem, the subgradient projection method based on dual decomposition is employed. Then, a heuristic algorithm is designed for the TDM mode wireless multi-hop networks by minimizing the discrepancy between the expected network cost and the optimal one in each timeslot. At last, the source–destination session rate and network utility are evaluated in a dedicated wireless multi-hop network scenario. The numerical results demonstrate that the session rates convergence and the network utility is improved by our proposed scheme.