Jimali Software Engineering

This paper presents a framework for authoring, storing, retrieving, and presenting music lectures on the Web. For a synchronized presentation between score and recorded performance audio, we propose a dynamic programming-based algorithm for MIDI-to-Wave alignment to explore the temporal relations between MIDI and the corresponding performance recording. With rapid advances in music transcription technology, it had become more possible to align MIDI and wave in a symbolic domain. However, transcription errors usually occur when transcribing polyphonic music or multi-instruments music because the complex harmonic of different instruments. The proposed alignment algorithm works in the symbolic domain even if many transcription errors have occurred. The aligned MIDI and wave can be attached to many kinds of teaching materials. With a synchronized presentation, learners can read music scores and get instructional information when listening to certain sections of music pieces. We built an evaluation system for doing a subjective evaluation. The percentage of bars which were regarded as aligned perfectly and aligned within acceptable limits is 97.08#x0025;. The questionnaire in the evaluation system also reported positive opinions from both engineers and musicians.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=5eb5c3e75aa3ebbd9decb5f94c4712f9p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=5eb5c3e75aa3ebbd9decb5f94c4712f9p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In the past decade, mature video processing and Internet technologies have made video services over IP feasible and increasingly popular, e.g., video-on-demand (VoD) and IPTV. Considering mobile life over heterogeneous networks, a user can exploit any device to enjoy/share pictures, videos and music at anytime and anywhere, and he may change his currently used device or attached network to another one. To manage video streaming sessions among heterogeneous networks and devices, we developed a Ubiquitous Multimedia Service Platform for Mobile Life over the Digital Home Environment (UMS-MLDH) in a 3-year (2006-2009) National Telecommunication Project (NTP). Many distinct-domains#x02C7; core techniques are devised and well integrated in UMS-MLDH, including session mobility management, session signaling and communication and adaptive layered video streaming over a 3-tier server-proxy-client network architecture. In our experiments, the system integration, implementation and merits of UMS-MLDH are exhibited over a hybrid Home-Vehicular-Office network.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=5ec6469188df0a27f62d6210446878ecp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=5ec6469188df0a27f62d6210446878ecp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

IEEE MultiMediabr clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=7d0a6173168150419ae9cd82fbb3ab39p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=7d0a6173168150419ae9cd82fbb3ab39p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Resource poverty is a fundamental constraint that severely limits the class of applications that can be run on mobile devices. We present a vision of mobile computing that breaks free of this fundamental constraint. In this vision, mobile users seamlessly utilize nearby computers to obtain the resource benefits of cloud computing without incurring WAN delays and jitter. Rather than relying on a distant "cloud," a mobile user instantiates a "cloudlet" on nearby infrastructure and uses it via a wireless LAN. Crisp interactive response for immersive applications that augment human cognition is then much easier to achieve because of the proximity of the cloudlet. We confirm that a critical aspect of this vision, namely rapid customization of cloudlet infrastructure, is achievable through dynamic VM synthesis.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=0d15107c77ae2faa8b755610accdeae0p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=0d15107c77ae2faa8b755610accdeae0p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

The Smartphone application market is expected to continue to grow at even higher rates and keeping high levels of quality will be a key factor for successful growth. The community of mobile developers is attracting members from other environments with mobile version initiatives for languages like Python or Ruby. But developing mobile applications requires facing mobile specific constraints and issues. With current development environments and profiling tools, it is highly difficult to deal with mobile communication issues: the main problems appear when using actual devices in real operations instead of emulators. We introduce a tool that aims to fill that gap by providing developers with the means to analyze mobile data communications. The key novelty of the profiling tool introduced in this paper is the correlation of traffic information, radio access technology measurements and location data, which helps third party developers test and evaluate their mobile applications in the field.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=8a578d784902fd38f3d42c0075be0a26p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=8a578d784902fd38f3d42c0075be0a26p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

2009-11-09 / 2009-11-11; Merida, Yucatan, Mexico; 2009 Latin American Web Congress (la-web 2009)br clear=both style=clear: both;/ br clear=both style=clear: both;/ hr / div style=font-size:xx-small;color:gray;padding-bottom:.5emPresented By:/div diva href=http://ads.pheedo.com/feeds/ht.php?t=camp;i=f1cee0dcb4e89189b7656440a2a2b636amp;p=1NEC/a/div table border=0 cellpadding=0 cellspacing=0 trtd valign=topobject id=flashObj width=486 height=412 classid=clsid:D27CDB6E-AE6D-11cf-96B8-444553540000 codebase=http://download.macromedia.com/pub/shockwave/cabs/flash/swflash.cab#version=9,0,47,0param name=movie value=http://c.brightcove.com/services/viewer/federated_f9/34448608001?isVid=1publisherID=1660622131 /param name=bgcolor value=#FFFFFF /param name=flashVars value=@videoPlayer=34442231001playerID=34448608001domain=embed /param name=base value=http://admin.brightcove.com /param name=seamlesstabbing value=false /param name=allowFullScreen value=true /param name=swLiveConnect value=true /param name=allowScriptAccess value=always /embed src=http://c.brightcove.com/services/viewer/federated_f9/34448608001?isVid=1publisherID=1660622131 bgcolor=#FFFFFF flashVars=@videoPlayer=34442231001playerID=34448608001domain=embed base=http://admin.brightcove.com name=flashObj width=300 height=250 seamlesstabbing=false type=application/x-shockwave-flash allowFullScreen=true swLiveConnect=true allowScriptAccess=always pluginspage=http://www.macromedia.com/shockwave/download/index.cgi?P1_Prod_Version=ShockwaveFlashHSPACE=10 align=left //embed/objectbr /a href=http://www.nec.com/global/cases/rms/?cid=bn58 target=_blankimg src=http://images.pheedo.com/g/nec/videologo.png border=0 //a/td/tr trtdnbsp;/td/tr /table div style=font-size:xx-small; padding-top: 1em;span style=border-top: 1px solid br style=display:none/ a href=http://www.pheedo.com/Ads by Pheedo/a /spanimg alt= style=border: 0; height: 1px; width: 1px; border=0 height=1 width=1 src=http://ads.pheedo.com/feeds/ht.php?t=vamp;i=f1cee0dcb4e89189b7656440a2a2b636amp;p=1/ img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/br/ /div

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/