Jimali Software Engineering

Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide fault-tolerance with higher network connectivity in {\em heterogeneous} wireless sensor networks, where sensor nodes possess different transmission radii. Such problems can be categorized as: (1) {\em full} fault-tolerance, which aims to deploy a minimum number of relay nodes to establish $k$ $(k \geq 1)$ vertex-disjoint paths between every pair of sensor and/or relay nodes; (2) {\em partial} fault-tolerance, which aims to deploy a minimum number of relay nodes to establish $k$ $(k \geq 1)$ vertex-disjoint paths only between every pair of sensor nodes. Due to the different transmission radii of sensors, these problems are further complicated by the existence of two different kinds of communication paths, namely {\em two-way} paths, along which wireless communications exist in both directions; and {\em one-way} paths, along which wireless communications exist in only one direction. This paper comprehensively analyzes the range of problems introduced by the different levels of fault-tolerance coupled with the different types of path, and presents approximation algorithms.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=a4a04559e7829d820c2817da1f5cb590p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=a4a04559e7829d820c2817da1f5cb590p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Recently, there has been a growing interest of using network coding to improve the performance of wireless networks, for example, authors of \cite{xor} proposed the practical wireless network coding system called COPE, which demonstrated the throughput gain achieved by network coding. However, COPE has two fundamental limitations: (a) the coding opportunity is crucially dependent on the established routes; (b) the coding structure in COPE is limited within a two-hop region only. The aim of this paper is to overcome these limitations. In particular, we propose DCAR, the Distributed Coding-Aware Routing mechanism which enables (1) the discovery for available paths between a given source and destination, and (2) the detection for potential network coding opportunities over much wider network region. On interesting result is that DCAR has the capability to discover high throughput paths with coding opportunities while conventional wireless network routing protocols fail to do so. In addition, DCAR can detect coding opportunities on the entire path, thus eliminating the "two-hop" coding limitation in COPE. We also propose a novel routing metric called Coding-aware Routing Metric (CRM) which facilitates the performance comparison between "coding-possible" and "coding-impossible" paths. We implement the DCAR system in ns-2 and carry out extensive evaluation.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=f2334e7a2a34133f744d9560ff44f8a4p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=f2334e7a2a34133f744d9560ff44f8a4p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Existing code update protocols for reprogramming nodes in a sensor network are either unsuitable or inefficient when used in a mobile environment. In this paper, we propose ReMo, an energy efficient, multihop reprogramming protocol for mobile sensor networks. Without making any assumptions on the location of nodes, ReMo uses the LQI and RSSI measurements of received packets to estimate link qualities and relative distances with neighbors in order to select the best node for code exchange. The protocol is based on a probabilistic broadcast paradigm with the mobile nodes smoothly modifying their advertisement transmission rates based on the dynamic changes in network density, thereby saving valuable energy. Contrary to previous protocols, ReMo downloads pages regardless of their order, thus, exploiting the mobility of the nodes and facilitating a fast transfer of the code. Our simulation results show significant improvement in reprogramming time and number of message transmissions over other existing protocols under different settings of network mobility. Our implementation results of ReMo on a testbed of SunSPOTs also showcase its better performance than existing reprogramming protocols in terms of transfer time and number of message transmissions.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=8e7023ca19af52ec3ea6cf5f176874a8p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=8e7023ca19af52ec3ea6cf5f176874a8p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

The key feature of many emerging pervasive applications is to proactively provide services to mobile individuals. One major challenge in providing users with proactive services lies in continuously monitoring users#x2019; context based on numerous sensors in their PAN/BAN environments. The context monitoring in such environments imposes heavy workloads on mobile devices and sensor nodes with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the mobile device can proactively understand users#x2019; contexts and react appropriately. This paper proposes a novel context monitoring approach that provides efficient processing and sensor control mechanisms. We implement and test a prototype system on two mobile devices: a UMPC and a wearable device with a diverse set of sensors. Example applications are also developed based on the implemented system. Experimental results show that SeeMon achieves a high level of scalability and energy efficiency.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=81d4e9810422931502ad0609282b86d4p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=81d4e9810422931502ad0609282b86d4p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Many recent advances in MAC protocols for wireless sensor networks have been proposed to reduce idle listening, an energy wasteful state of the radio. Low-Power-Listening (LPL) protocols transmit packets for t_i s (the "inter-listening interval"), thereby allowing nodes to sleep for long periods of time between channel probes. The inter-listening interval as well as the particular type of LPL protocol should be well matched to the network conditions. In this paper, we propose network-aware adaptation of the specific succession of repeated packets over the t_i interval (the "MAC schedule"), which yields significant energy savings. Moreover, some LPL protocols interrupt communication between the sender and the receiver after the data packet has been successfully received. We propose a new and simple adaptation of the "transmit / receive schedule" to synchronize nodes on a slowly changing path so that energy consumption and delay are further reduced, at no cost of overhead in most cases. Our results show that using network-aware adaptation of the MAC schedule provides up to 30% increase in lifetime for different traffic scenarios. Additional adaptation of the transmit / receive schedule to automatically synchronize the nodes can reduce packet delivery delays by up to 50%, providing an additional decrease in energy consumption of 18%br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=eb85e2b4b599706138c10a3485335f30p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=eb85e2b4b599706138c10a3485335f30p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In recent years, multiple power saving (PS) protocols have been proposed in the 802.11 standards to save energy for mobile devices. Many works have been carried out on testbeds or simulation platforms to evaluate their performances. However, there is a lack of accurate theoretical models to analyze the performance for these protocols. In an effort to fill this gap, we present a Markov chain based model to analytically study these PS protocols, with its focus on multicast services. The proposed model successfully captures the key characteristic of the power saving systems: the data delivery procedure starts periodically at the previously negotiated time, but ends at a rather random time with its distribution depending on the ending time of data delivery in the last delivery period and the the arrival rate of incoming traffic. Under the poisson assumption for incoming traffic and in light to moderate traffic loads, the amount of data delivered between consecutive delivery periods possesses the Markov property, which builds up our Markov chain model. For incoming traffic with long range dependence, a multi-state Markov Modulated Poisson Process (MMPP) is used to approximate the traffic, making the model valid in more general cases.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=e03e211e4e707eeea257018ccbc979b6p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=e03e211e4e707eeea257018ccbc979b6p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Location and inter-sensor distance estimations are important functions for the operation of wireless sensor networks, especially when protocols can benefit from the distance information prior to network deployment. The maximum multihop distance that can be covered in a given number of hops in a sensor network is one such parameter related with coverage area, delay, and minimal multihop transmission energy consumption estimations. In randomly deployed sensor networks, inter-sensor distances are random variables. Hence, their evaluations require probabilistic methods, and distance models should involve investigation of distance distribution functions. Current literature on analytical modeling of the maximum distance distribution is limited to one-dimensional networks using the Gaussian pdf. However, determination of the maximum multihop distance distribution in two dimensional networks is a quite complex problem. Furthermore, distance distributions in two dimensional networks are not accurately modeled by the Gaussian pdf. Hence, we propose a greedy method of distance maximization and evaluate the distribution of the obtained multihop distance through analytical approximations and simulations.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=c66faa4b07720bafa8885528e8399780p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=c66faa4b07720bafa8885528e8399780p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Emerging dual-mode phones incorporate a Wireless LAN (WLAN) interface along with the traditional cellular interface. The additional benefits of the WLAN interface are, however, likely to be outweighed by its greater rate of energy consumption. This is especially of concern when real-time applications, that result in continuous traffic, are involved. WLAN radios typically conserve energy by staying in sleep mode. With real-time applications like Voice over Internet Protocol (VoIP), this can be challenging since packets delayed above a threshold are lost. Moreover, the continuous nature of traffic makes it difficult for the radio to stay in the lower power sleep mode enough to reduce energy consumption significantly. In this work we propose the GreenCall algorithm to derive sleep/wakeup schedules for the WLAN radio to save energy during VoIP calls while ensuring that application quality is preserved within acceptable levels of users. We evaluate GreenCall on commodity hardware and study its performance over diverse network paths and describe our experiences in the process. We further extensively investigate the effect of different application parameters on possible energy savings through trace-based simulations. We show that, in spite of the interactive, real-time nature of voice, energy consumption during calls can be reduced by close to 80% in most instances.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=f68adb0d90484dffb12d90a856275d93p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=f68adb0d90484dffb12d90a856275d93p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Localization is an essential and important research issue in wireless sensor networks (WSNs). Most localization schemes focus on static sensor networks. However, mobile sensors are required in some applications such that the sensed area can be enlarged. As such, a localization scheme designed for mobile sensor networks is necessary. In this paper, we propose a localization scheme to improve the localization accuracy of previous work. In this proposed scheme, the normal nodes without location information can estimate their own locations by gathering the positions of location-aware nodes (anchor nodes) and the one-hop normal nodes whose locations are estimated from the anchor nodes. In addition, we propose a scheme that predicts the moving direction of sensor nodes to increase localization accuracy. Simulation results show that the localization error in our proposed scheme is lower than the previous schemes in various mobility models and moving speeds.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=b8d2cb56d3bbd59d363a1f0300d2cee8p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=b8d2cb56d3bbd59d363a1f0300d2cee8p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In this paper, a novel scheme for Cognitive Radio (CR) spectrum sensing in Medium Access Control (MAC) layer, called Extended Knowledge-Based Reasoning (EKBR), is proposed. The target of EKBR is to improve the fine sensing efficiency by jointly considering a number of network states and environmental statistics, including fast sensing results, short-term statistical information, channel quality, data transmission rate, and channel contention characteristics. This is for a better estimation on the optimal range of spectrum for fine sensing so as to adaptively reduce the overall channel sensing time. Performance analysis is conducted on the proposed EKBR scheme using a multi-dimensional absorbing Markov chain to evaluate various performance metrics of interest, such as average sensing delay (or referred to as sensing overhead in the study), average data transmission rate, and percentage of missed spectrum opportunities. Numerical results show that the proposed EKBR scheme achieves better performance than that by the state-or-the-art techniques while yielding less computation complexity and sensing overhead.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=6156bf795782df1c256e076cf383f731p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=6156bf795782df1c256e076cf383f731p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Global barrier coverage is known to be an appropriate model of coverage for movement detection applications such as intrusion detection. However, it has been proved that given a sensor deployment, sensors cannot locally determine whether the deployment provides global barrier coverage, making it impossible to develop localized algorithms. In this paper, we introduce the concept of local barrier coverage to address this limitation. Motivated by the observation that movements are likely to follow a shorter path in crossing a belt region, local barrier coverage guarantees the detection of all movements whose trajectory is confined to a slice of the belt region of deployment. We prove that it is possible for individual sensors to locally determine the existence of local barrier coverage. Although local barrier coverage does not deterministically guarantee global barrier coverage, we show that for thin belt regions, local barrier coverage almost always provides global barrier coverage. To demonstrate that local barrier coverage can be used to design localized algorithms, we develop a novel sleep-wakeup algorithm for maximizing the network lifetime, called Localized Barrier Coverage Protocol (LBCP). We prove that LBCP guarantees local barrier coverage and show that LBCP provides close to optimal enhancement in the network lifetime, while providing global barrier coverage most of the time.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=b9f013f63fc6a97680ea126000ba9eddp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=b9f013f63fc6a97680ea126000ba9eddp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Third Generation (3G) cellular networks take advantage of time-varying and location-dependent channel conditions of mobile users to provide broadband services. They use opportunistic scheduling to utilize spectrum efficiently under fairness and QoS constraints. Opportunistic scheduling algorithms rely on the collaboration among all mobile users to achieve their design objectives. However, we demonstrate that rogue cellular devices can exploit vulnerabilities in popular opportunistic scheduling algorithms, such as Proprotional Fair (PF) and Temporal Fair (TF), to usurp the majority of time slots in 3G networks. Our simulations show that only five rogue device per 50-user cell can use up to 90% of the time slots, and can cause two-second end-to-end inter-packet transmission delay on VoIP applications for every user in the same cell, rendering VoIP applications useless. To defend against this attack, we propose strengthening the PF and TF schedulers and a robust handoff scheme.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=98b9179359c213000717bf4713e333eep=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=98b9179359c213000717bf4713e333eep=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

We explore the use of clock skew of a wireless local area network access point (AP) as its fingerprint to detect unauthorized APs quickly and accurately. The main goal behind using clock skews is to overcome one of the major limitations of existing solutions- the inability to effectively detect Medium Access Control (MAC) address spoofing. We calculate the clock skew of an AP from the IEEE 802.11 Time Synchronization Function (TSF) timestamps sent out in the beacon/probe response frames. We use two different methods for this purpose - one based on linear programming and the other based on least square fit. We collect TSF timestamp data from several APs in three different residential settings. Using our measurement data as well as data obtained from a large conference setting, we find that clock skews remain consistent over time for the same AP but vary significantly across APs. Furthermore, we improve the resolution of received timestamp of the frames and show that with this enhancement our methodology can find clock skews very quickly, using 50-100 packets in most of the cases. We also discuss and quantify the impact of various external factors including temperature variation, virtualization, clock source selection and NTP synchronization on clock skews.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=eac47f9e051fbe9583d68711e0df9bd4p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=eac47f9e051fbe9583d68711e0df9bd4p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Throughput optimization in wireless networks with multiple channels and multiple radio interfaces per node is a challenging problem. For general traffic models (given a set of source-destination pairs), optimization of throughput entails design of "efficient" routes between the given source-destination pairs, in conjunction with (i) assignment of channels to interfaces and communication links, and (ii) scheduling of non-interfering links for simultaneous transmission. Prior work has looked at restricted versions of the above problem. In this article, we design approximation algorithms for the joint routing, channel assignment, and link scheduling problem in wireless networks with general interference models. The unique contributions of our work include addressing the above joint problem in the context of physical interference model and single-path routing (wherein, traffic between a source-destination is restricted to a single path). To the best of our knowledge, ours is the first work to address the throughput maximization problem in such general contexts. For each setting, we design approximation algorithms with provable performance guarantees. We demonstrate the effectiveness of our algorithms in general contexts through simulations.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=2195f60b6c7f2b77c821eaa1b3a3fefap=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=2195f60b6c7f2b77c821eaa1b3a3fefap=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In this paper, we study optimal deployment in terms of sensor number needed to achieve four connectivity and full coverage under different ratios of sensors' communication range (denoted by $r_c$) to their sensing range (denoted by $r_s$). We propose a new pattern called the "Diamond" pattern, which can be viewed as a series of evolving patterns. When $r_c/r_s \ge \sqrt{3}$, the Diamond pattern coincides with the well-known triangle lattice pattern; when $r_c/r_s \leq \sqrt{2}$, it degenerates to a "Square" pattern (i.e., square grid). We prove that the pattern we propose is asymptotically optimal when $r_c/r_s \sqrt{2}$ to achieve four connectivity and full coverage. We also discover another new deployment pattern called the ``Double-strip'' pattern. This pattern broadens the research on optimal deployment patterns from a new aspect. Our work is the first to propose an asymptotically optimal deployment pattern to achieve four connectivity and full coverage for WSNs. Our work also provides insights on how optimal patterns evolve and how to search for them.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=8aa282b4ba4ac531cf363f4c4d72afacp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=8aa282b4ba4ac531cf363f4c4d72afacp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

For non-cooperative networks in which each node is a selfish agent, certain incentives must be given to intermediate nodes to let them forward the data for others. What makes the scenario worse is that, in a multi-hop non-cooperative network, the endpoints can only observe whether or not the end-to-end transaction was successful or not, but not the individual actions of intermediate nodes. Thus, in the absence of properly designed incentive schemes, rational and selfish intermediate nodes may choose to forward data packets at a very low priority or simply drop the packets, and they could put the blame on the unreliable channel. In this paper, assuming the receiver is a trusted authority, we propose several methods that discourage the hidden actions under hidden information in multi-hop non-cooperative networks with high probability. We design several algorithmic mechanisms for a number of routing scenarios such that each selfish agent will maximize its expected utility (\ie, profit) when it \emph{truthfully} declares its \emph{type} (\ie, cost and its actions) and it truthfully follows its declared actions. Our simulations show that the payments by our mechanisms are only slightly larger than the \emph{actual cost} incurred by all intermediate nodes.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=24f7bd7ee200dc6edb9bdf08bc15fc96p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=24f7bd7ee200dc6edb9bdf08bc15fc96p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Indoor positioning is an enabling technology for delivery of location-based services in mobile computing environments. This paper proposes a positioning solution using received signal strength in indoor Wireless Local Area Networks. In this application, an explicit measurement equation and the corresponding noise statistics are unknown because of the complexity of the indoor propagation channel. To address these challenges, we introduce a new state-space Bayesian filter: the Nonparametric Information (NI) filter. This filter effectively tracks motion in situations where the Kalman filter and its variants are inapplicable, while maintaining a computational complexity comparable to that of the Kalman filter. To deal with the noisy nature of the indoor propagation environment, the NI filter is used in the design of an intelligent dynamic WLAN tracking system. The system anticipates future position values and adapts its sensing and estimation parameters accordingly. Our experimental results conducted on measurements from a real office environment indicate that the combination of the intelligent design and the NI filter results in significant improvements over the Kalman and particle filters.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=69e9b5a78d1c938a876d9be6b201e263p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=69e9b5a78d1c938a876d9be6b201e263p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

We consider a wireless basestation serving users through time-varying channels. It is well-known that opportunistic scheduling with full channel state information (CSI) is throughput-optimal. However, it may not be energy-efficient when the cost of channel acquisition is high and traffic rates are low. Under the low traffic rate regime, it may be sufficient and more energy-efficient to transmit data without CSI, since no channel acquisition power is consumed. In general, we show strategies that probe channels in every slot or never probe channels in any slot are not necessarily optimal, and we must consider mixed strategies. We derive a unified scheduling algorithm that dynamically chooses to transmit data with full or no CSI based on queue backlog and channel statistics. Our methodology is general and can be extended to include timing overhead due to channel acquisition, and to treat systems that allow any subset of channels to be measured. Through Lyapunov analysis, we show our algorithm is throughput-optimal and stabilizes the downlink with optimal power consumption, regardless of the values of channel probing power, transmission power, and data rates. Through simulations, we show our algorithm is energy-efficient by balancing well between earning opportunistic scheduling gains in channel-aware mode and saving channel probing power in channel-blind mode.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=fb40c9f8434d0536c69307ba1518becbp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=fb40c9f8434d0536c69307ba1518becbp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Most users in a mobile environment are moving and accessing wireless services for the activities they are currently engaged in. We propose the idea of complex activity for characterizing the continuously changing complex behavior patterns of mobile users. For the purpose of data management, a complex activity is modeled as a sequence of location movement, service requests, the co-occurrence of location and service pair, or the interleaving of all above. An activity may be composed of subactivities. Different activities may exhibit dependencies that affect user behaviors. We argue that the complex activity concept provides a more precise, rich, and detail description of user behavioral patterns which are invaluable for data management in mobile environments. Proper exploration of user activities has the potential of providing much higher quality and personalized services to individual user at the right place and on the right time. We therefore propose new methods for complex activity mining, incremental maintenance, online detection and proactive data management based on user activities. In particular, we devise prefetching and pushing techniques with cost sensitive control to facilitate predictive data allocation. Preliminary implementation and simulation results demonstrate that the proposed framework and techniques can significantly increase local availability, conserve execution cost, reduce response time and improve cache utilization.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=2e89fc50d4f32afe415b697f96567886p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=2e89fc50d4f32afe415b697f96567886p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In wireless networks, node cooperation is usually exploited as a data relaying mechanism. However, the wireless channel allows for much richer interaction between nodes. In a multi-channel scenario, transmitter-receiver pairs may make incorrect decisions (e.g., in selecting channels) but idle neighbors could help by sharing information to prevent data collisions. This is a Distributed Information SHaring (DISH) approach to cooperation and suggests new ways of designing cooperative protocols. However, what is lacking is a theoretical understanding of this new notion of cooperation. In this paper, we view cooperation as a network resource and evaluate the probability of obtaining cooperation, $p_{co}$. First, we analytically evaluate $p_{co}$ in the context of multi-channel multi-hop wireless networks. Second, we verify the analysis via simulations, showing that our analysis accurately characterizes the behavior of $p_{co}$ as a function of underlying network parameters. Third, we investigate the correlation between $p_{co}$ and network performance in terms of collision rate, packet delay, and throughput. We find a near-linear relationship, which suggests that $p_{co}$ be used as an appropriate performance indicator itself. Finally, we apply our analysis to solving a channel bandwidth allocation problem, where we derive optimal schemes and provide general guidelines on bandwidth allocation for DISH networks.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=b15bc615fdcc199349008e2ee4dff2f4p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=b15bc615fdcc199349008e2ee4dff2f4p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/