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Mobile Computing, IEEE Transactions on

Issue 8 • Date Aug. 2014

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Displaying Results 1 - 21 of 21
  • A Novel Unified Analytical Model for Broadcast Protocols in Multi-Hop Cognitive Radio Ad Hoc Networks

    Page(s): 1653 - 1667
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1626 KB) |  | HTML iconHTML  

    Broadcast is an important operation in wireless ad hoc networks where control information is usually propagated as broadcasts for the realization of most networking protocols. In traditional ad hoc networks, since the spectrum availability is uniform, broadcasts are delivered via a common channel which can be heard by all users in a network. However, in cognitive radio (CR) ad hoc networks, different unlicensed users may acquire different available channels depending on the locations and traffic of licensed users. This non-uniform channel availability leads to several significant differences and causes unique challenges when analyzing the performance of broadcast protocols in CR ad hoc networks. In this paper, a novel unified analytical model is proposed to address these challenges. Our proposed analytical model can be applied to any broadcast protocol with any CR network topology. We propose to decompose an intricate network into several simple networks which are tractable for analysis. We also propose systematic methodologies for such decomposition. Results from both the hardware implementation and software simulation validate the analysis well. To the best of our knowledge, this is the first analytical work on the performance analysis of broadcast protocols for multi-hop CR ad hoc networks. View full abstract»

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  • A Session-Based Mobile Socket Layer for Disruption Tolerance on the Internet

    Page(s): 1668 - 1680
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2090 KB) |  | HTML iconHTML  

    Several existing IP mobility solutions use invasive approaches, when adjustments in legacy protocols from the TCP/IP stack are necessary, or rely on specific network infrastructures. We devised an architecture to handle mobility using a Session-based Mobile Socket Layer (SMSL). With no need for software adaptation in the core of the network or adjustment on the TCP/IP stack, SMSL operates only at the end systems involved in the communication, being fully transparent to neighboring Transport and Application layers. The session scheme allows mobility awareness for TCP-based applications that require resilience to failures, delays, or disconnection. A general-purpose API extended from the Socket and implemented in GNU/Linux provides session services, such as tracking mobile peers, detecting disruptions, and suspending and resuming sessions with efficiency, security, and reliability. In this paper, we present the entire session support system as a mature work of research achieved with advances made in our previous study. The results of experiments in real and emulated test environments demonstrate efficiency. SMSL introduces little overhead, with a mean goodput degradation of 6.9% compared to an application implemented on top of the standard TCP/IP stack. Disruptions are detected in microseconds and suspended sessions resume in milliseconds for single-homed mobile nodes. View full abstract»

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  • Adaptive and Energy Efficient Context Representation Framework in Mobile Sensing

    Page(s): 1681 - 1693
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (924 KB) |  | HTML iconHTML  

    This paper presents a novel framework that includes an inhomogeneous (time-variant) Hidden Markov Model (HMM) and learning from data concepts. The framework either recognizes or estimates user contextual inferences called `user states' within the concept of Human Activity Recognition (HAR) for future context-aware applications. Context-aware applications require continuous data acquisition and interpretation from one or more sensor reading(s). Therefore, device battery lifetimes need to be extended due to the fact that constantly running built-in sensors deplete device batteries rapidly. In this sense, a framework is constructed to fulfill requirements needed by applications and to prolong device battery lifetimes. The ultimate goal of this paper is to present an accurate user state representation model, and to maximize power efficiency while the model operates. Most importantly, this research intends to create and clarify a generic framework to guide the development of future context-aware applications. Moreover, topics such as user profile adaptability and variant sensory sampling operations are examined. The proposed framework is validated by simulations and implemented in a HAR-based application by the smartphone accelerometer. According to the results, the proposed framework shows an increase in power efficiency of 60% for an accuracy range from 75% up to 96%, depending on user profiles. View full abstract»

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  • Adaptive Duty Cycling for Place-Centric Mobility Monitoring using Zero-Cost Information in Smartphone

    Page(s): 1694 - 1706
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2605 KB) |  | HTML iconHTML  

    Smartphones enable the collection of mobility data using various sensors. The key challenge in the collection of continuous data is to overcome the limited battery capacity of the device. While extensive research has been conducted to solve energy issues in continuous mobility learning, we argue that previous works have not reached optimal performance. In this paper, we propose an energy-efficient mobility monitoring system, FreeTrack, to collect place-centric mobility data with minimum energy consumption in everyday life. We first analyzed the regularity of life patterns, cellular connection patterns, and battery charging behaviors of 94 smartphone users to examine important features related to human mobility. Based on our findings, we design an adaptive duty cycling scheme that uses zero-cost information (i.e., regular mobility, cell connection, and battery state) as low-level sensing to infer location change without the need to activate sensors. We model the location inference on the Hidden Markov Model and optimize the sensing schedule of individual smartphones for real-time operation. Our extensive experiment with 48 smartphone users shows that the proposed system achieves an energy saving of about 68% over previous works, yet still correctly traces 97% of mobility with 0.2±0.5 places misses in a day. View full abstract»

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  • ARC: Adaptive Reputation based Clustering Against Spectrum Sensing Data Falsification Attacks

    Page(s): 1707 - 1719
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1355 KB) |  | HTML iconHTML  

    IEEE 802.22 is the first standard based on the concept of cognitive radio. It recommends collaborative spectrum sensing to avoid the unreliability of individual spectrum sensing while detecting primary user signals. However, it opens an opportunity for attackers to exploit the decision making process by sending false reports. In this paper, we address security issues regarding distributed node sensing in the 802.22 standard and discuss how attackers can modify or manipulate their sensing result independently or collaboratively. This problem is commonly known as spectrum sensing data falsification (SSDF) attack or Byzantine attack. To counter the different attacking strategies, we propose a reputation based clustering algorithm that does not require prior knowledge of attacker distribution or complete identification of malicious users. We provide an extensive probabilistic analysis of the performance of the algorithm. We compare the performance of our algorithm against existing approaches across a wide range of attacking scenarios. Our proposed algorithm displays a significantly reduced error rate in decision making in comparison to current methods. It also identifies a large portion of the attacking nodes and greatly minimizes the false detection rate of honest nodes. View full abstract»

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  • Context-Aware Energy Enhancements for Smart Mobile Devices

    Page(s): 1720 - 1732
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2207 KB) |  | HTML iconHTML  

    Within the past decade, mobile computing has morphed into a principal form of human communication, business, and social interaction. Unfortunately, the energy demands of newer ambient intelligence and collaborative technologies on mobile devices have greatly overwhelmed modern energy storage abilities. This paper proposes several novel techniques that exploit spatiotemporal and device context to predict device wireless data and location interface configurations that can optimize energy consumption in mobile devices. These techniques, which include variants of linear discriminant analysis, linear logistic regression, non-linear logistic regression with neural networks, k-nearest neighbor, and support vector machines are explored and compared on synthetic and user traces from real-world usage studies. The experimental results show that up to 90% successful prediction is possible with neural networks and k-nearest neighbor algorithms, improving upon prediction strategies in prior work by approximately 50%. Further, an average improvement of 24% energy savings is achieved compared to state-of-the-art prior work on energy-efficient location-sensing. View full abstract»

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  • IVC in Cities: Signal Attenuation by Buildings and How Parked Cars Can Improve the Situation

    Page(s): 1733 - 1745
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1310 KB) |  | HTML iconHTML  

    We study the effectiveness of Inter-Vehicle Communication (IVC) in urban and suburban environments at low node densities, with a particular focus on cooperative awareness and traffic safety. The recently standardized DSRC/WAVE protocol suite defines a platform for such applications, which mainly focus on beaconing, i.e., periodic 1-hop-broadcast. In general, such safety relevant transmissions are defined by time criticality. One of the major problems to be solved is how to tackle the very difficult and complex radio signal attenuation due to buildings and other obstacles, especially in cities. Typical concepts address this problem by requiring all vehicles to also act as relays or by using dedicated Roadside Units (RSUs). We show how such systems may be operated more efficiently and how the situation can be further improved by relying on parked vehicles in addition to, or as a replacement for, RSUs. Given the fact that the U.S. DOT is already evaluating whether to make DSRC mandatory for new cars, wide availability of radio equipped cars can be predicted; also the impact in terms of energy consumption is negligible. We performed an extensive set of simulations to evaluate the negative impact of buildings at low node densities and the benefit of our proposal. Our results clearly indicate that situation awareness can be significantly improved. When disseminating safety critical events in a realistic scenario, reasonable numbers of parked cars can increase cooperative awareness by up to 25%, a factor which requires an unreasonably costly number of RSUs. To the best of our knowledge, we are the first to propose the utilization of parked vehicles as relay nodes for safety applications in vehicular networks. View full abstract»

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  • Modeling, Evaluation and Detection of Jamming Attacks in Time-Critical Wireless Applications

    Page(s): 1746 - 1759
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1349 KB) |  | HTML iconHTML  

    Recently, wireless networking for emerging cyber-physical systems, in particular the smart grid, has been drawing increasing attention in that it has broad applications for time-critical message delivery among electronic devices on physical infrastructures. However, the shared nature of wireless channels unavoidably exposes the messages in transit to jamming attacks, which broadcast radio interference to affect the network availability of electronic equipments. An important, yet open research question is how to model and detect jamming attacks in such wireless networks, where communication traffic is more time-critical than that in conventional data-service networks, such as cellular and WiFi networks. In this paper, we aim at modeling and detecting jamming attacks against time-critical wireless networks with applications to the smart grid. In contrast to communication networks where packets-oriented metrics, such as packet loss and throughput are used to measure the network performance, we introduce a new metric, message invalidation ratio, to quantify the performance of time-critical applications. Our modeling approach is inspired by the similarity between the behavior of a jammer who attempts to disrupt the delivery of a time-critical message and the behavior of a gambler who intends to win a gambling game. Therefore, by gambling-based modeling and real-time experiments, we find that there exists a phase transition phenomenon for successful time-critical message delivery under a variety of jamming attacks. That is, as the probability that a packet is jammed increases from 0 to 1, the message invalidation ratio first increases slightly, then increases dramatically to 1. Based on analytical and experimental results, we design the Jamming Attack Detection based on Estimation (JADE) scheme to achieve robust jamming detection, and implement JADE in a wireless network for power substations in the smart grid. View full abstract»

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  • Modeling Energy Consumption of Data Transmission Over Wi-Fi

    Page(s): 1760 - 1773
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1911 KB) |  | HTML iconHTML  

    Wireless data transmission consumes a significant part of the overall energy consumption of smartphones, due to the popularity of Internet applications. In this paper, we investigate the energy consumption characteristics of data transmission over Wi-Fi, focusing on the effect of Internet flow characteristics and network environment. We present deterministic models that describe the energy consumption of Wi-Fi data transmission with traffic burstiness, network performance metrics like throughput and retransmission rate, and parameters of the power saving mechanisms in use. Our models are practical because their inputs are easily available on mobile platforms without modifying low-level software or hardware components. We demonstrate the practice of model-based energy profiling on Maemo, Symbian, and Android phones, and evaluate the accuracy with physical power measurement of applications including file transfer, web browsing, video streaming, and instant messaging. Our experimental results show that our models are of adequate accuracy for energy profiling and are easy to apply. View full abstract»

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  • Monitoring Breathing via Signal Strength in Wireless Networks

    Page(s): 1774 - 1786
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1424 KB) |  | HTML iconHTML  

    This paper shows experimentally that standard wireless networks which measure received signal strength (RSS) can be used to reliably detect human breathing and estimate the breathing rate, an application we call “BreathTaking”. We present analysis showing that, as a first order approximation, breathing induces sinusoidal variation in the measured RSS on a link, with amplitude a function of the relative amplitude and phase of the breathing-affected multipath. We show that although an individual link may not reliably detect breathing, the collective spectral content of a network of devices reliably indicates the presence and rate of breathing. We present a maximum likelihood estimator (MLE) of breathing rate, amplitude, and phase, which uses the RSS data from many links simultaneously. We show experimental results which demonstrate that reliable detection and frequency estimation is possible with 30 seconds of data, within 0.07 to 0.42 breaths per minute (bpm) RMS error in several experiments. The experiments also indicate that the use of directional antennas may improve the systems robustness to external motion. View full abstract»

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  • Multiple Target Tracking with RF Sensor Networks

    Page(s): 1787 - 1800
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1718 KB) |  | HTML iconHTML  

    RF sensor networks are wireless networks that can localize and track people (or targets) without needing them to carry or wear any electronic device. They use the change in the received signal strength (RSS) of the links due to the movements of people to infer their locations. In this paper, we consider real-time multiple target tracking with RF sensor networks. We apply radio tomographic imaging (RTI), which generates images of the change in the propagation field, as if they were frames of a video. Our RTI method uses RSS measurements on multiple frequency channels on each link, combining them with a fade level-based weighted average. We introduce methods, inspired by machine vision and adapted to the peculiarities of RTI, that enable accurate and real-time multiple target tracking. Several tests are performed in an open environment, a one-bedroom apartment, and a cluttered office environment. The results demonstrate that the system is capable of accurately tracking in real-time up to four targets in cluttered indoor environments, even when their trajectories intersect multiple times, without mis-estimating the number of targets found in the monitored area. The highest average tracking error measured in the tests is 0.45 m with two targets, 0.46 m with three targets, and 0.55 m with four targets. View full abstract»

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  • Optimizing Small Cell Deployment in Arbitrary Wireless Networks with Minimum Service Rate Constraints

    Page(s): 1801 - 1815
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1431 KB) |  | HTML iconHTML  

    Femtocell technology has shifted beyond indoor residential applications to cover a wider range of scenarios including metropolitan and rural areas. The term “small cell” has hence been used to denote such low-power transmission points deployed for enhancing macrocell coverage and/or capacity. While deployment of femto BSs has typically followed the bottom-up paradigm driven by the ad hoc demand of users, more and more studies have prompted a move toward a more managed deployment model for better tradeoff between performance and cost. In this paper, we investigate an optimization problem for femtocell deployment in a dense network with arbitrary topology. The goal is to determine deployment locations and operation parameters of femtocells for maximizing the number of customers supported with QoS constraints. Since the formulated problem belongs to mixed-integer non-linear programming (MINLP), we propose an anytime algorithm that transforms the joint problem into a cluster formation sub-problem (involving location selection and cell coverage) and a resource management sub-problem (involving power control and resource allocation) for effectively solving all optimization variables in an iterative fashion. Compared with other approaches for femtocell deployment, our evaluation results show that the proposed algorithm can effectively solve the target problem while striking a better performance tradeoff between computation complexity and solution quality. View full abstract»

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  • Performance Modeling of Delay-Tolerant Network Routing via Queueing Petri Nets

    Page(s): 1816 - 1828
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2903 KB) |  | HTML iconHTML  

    With the advent of wireless technologies such as Wi-Fi Direct and Near Field Communication (NFC), infrastructure-less Peer-to-Peer (P2P) content sharing among mobile devices is set to become more ubiquitous. Delay-Tolerant Networks (DTNs), with their opportunistic message forwarding strategy, can be leveraged to provide seamless connectivity in such scenarios. To the best of our knowledge, little has been done to understand the performance of DTNs under realistic settings involving the interplay of diverse factors such as bundle fragmentation, scheduling, and buffer spacing. In this paper, we look at Queueing Petri Nets (QPNs) as a modeling framework to study the performance of DTN routing. We develop QPN models for DTNs of increasing complexity in an incremental fashion, starting from a network that employs the rudimentary direct transmission routing protocol to a network that employs a family of multi-hop and replication-based routing protocols (namely (p, q) -epidemic routing). The complete QPN model considers a number of realistic factors that impact performance such as finite buffer space, finite link bandwidth, bundles with different priorities and intra-scheduling delays arising due to different levels of the memory hierarchy at the nodes. We come up with a three-fold validation scheme to assert the veracity of our proposed models, via comparison of results obtained from simulations of the QPN vis-a-vis those obtained from direct simulation of the underlying DTN and experimental results obtained from a testbed of Android based devices that employ a mobility emulation scheme. We also show a case to exemplify the analytical capability of the QPN, by deriving the underlying reachability graph and constructing an equivalent stochastic jump process. We identify the stochastic process to be a Semi-Markov Process (SMP) and hence arrive at a closed form expression for the end-to-end delivery latency by computing the hitting time of the SMP. We find that the model ac- urately captures the behavior of a DTN in numerous realistic scenarios, showing the efficacy of QPNs as a suitable modeling framework for evaluating the DTN routing protocols. View full abstract»

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  • Power Efficient Ultra Wide Band Based Wireless Body Area Networks with Narrowband Feedback Path

    Page(s): 1829 - 1842
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    The basic requirement of wireless healthcare monitoring systems is to send physiological signals acquired from implantable or on-body sensor nodes to a remote location. Low-power consumption is required for wireless healthcare monitoring systems since most medical sensor nodes are battery powered. The emergence of new technologies in measuring physiological signals has increased the demand for high data rate transmission systems. Ultra-wide band (UWB) is a suitable wireless technology to achieve high data rates while keeping power consumption and form factors small. Although UWB transmitters are designed based on simple techniques, UWB receivers require complex hardware and consume comparatively higher power. In order to achieve reliable low power two-way communication, a sensor node can be constructed using a UWB transmitter and a narrow band receiver. This paper proposes a new medium access control (MAC) protocol based on a dual-band physical layer technology. Co-simulation models based on MATLAB and OPNET have been developed to analyze the performance of the proposed MAC protocol. We analyzed the performance of the MAC protocol for a realistic scenario where both implantable and wearable sensor nodes are involved in the data transmission. Priority-based packet transmission techniques have been used in the MAC protocol to serve different sensors according to their QoS requirements. Analysis is done with regard to important network parameters, such as packet loss ratio, packet delay, percentage throughput, and power consumption. View full abstract»

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  • Pricing, Spectrum Sharing, and Service Selection in Two-Tier Small Cell Networks: A Hierarchical Dynamic Game Approach

    Page(s): 1843 - 1856
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (902 KB) |  | HTML iconHTML  

    Small cells overlaid with macrocells can increase the capacity of two-tier cellular wireless networks by offloading traffic from macrocells. To motivate the small cell service providers (SSPs) to open portion of the access opportunities to macro users (i.e., to operate in a hybrid access mode), we design an incentive mechanism in which the macrocell service provider (MSP) could pay to the SSPs. According to the price offered by the MSP, the SSPs decide on the open access ratio, which is the ratio of shared radio resource for macro users and the total amount of radio resource in a small cell. The users in this two-tier network can make service selection decisions dynamically according to the performance satisfaction level and cost, which again depend on the pricing and spectrum sharing between the MSP and SSPs. To model this dynamic interactive decision problem, we propose a hierarchical dynamic game framework. In the lower level, we formulate an evolutionary game to model and analyze the adaptive service selection of users. An evolutionary stable strategy (ESS) is considered to be the solution of this game. In the upper level, the MSP and SSPs sequentially determine the pricing strategy and the open access ratio, respectively, taking into account the distribution of dynamic service selection at the lower-level evolutionary game. A Stackelberg differential game is formulated where the MSP and SSPs act as the leader and followers, respectively. An open-loop Stackelberg equilibrium is considered to be the solution of this game. We also extend the hierarchical dynamic game framework and investigate the impact of information delays on the equilibrium solutions. Numerical results show the effectiveness and advantages of dynamic control of the open access ratio and pricing. View full abstract»

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  • Real-Time Scheduling for Xen-ARM Virtual Machines

    Page(s): 1857 - 1867
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    This paper investigates the feasibility of real-time scheduling with mobile hypervisor, Xen-ARM. Particularly for mobile virtual machines, real-time support is in high demand. However, it is difficult to guarantee real-time scheduling with virtual machines because inter-VM and intra-VM schedulability have to be determined in multi-OS environments. To address the schedulability, first, this paper presents a definition of a real-time virtual machine. Second, this paper analyzes intra-VM schedulability, taking quantization overhead into account. Quantization overhead comes from tick-based scheduling of Xen-ARM, which requires integer presentation of scheduling period and execution slice. Third, to minimize quantization overhead, this paper provides a new algorithm, called SH-quantization that provides accurate and efficient parameterization of a real-time virtual machine. Fourth, this paper presents an inter-VM schedulability test for incorporating multiple real-time virtual machines. To evaluate the approach, we implement the SH-quantization algorithm in Xen-ARM and paravirtualize a real-time OS, called xeno-μC/OS-II. We ran extensive experiments with various configurations of real-time tasks on a real hardware platform in order to characterize the scheduling behavior of real-time virtual machine with quantization. The results show that quantization overhead consumes additional CPU bandwidth up to 90% and the proposed algorithm guarantees intra/inter-VM schedulability with minimal CPU bandwidth. View full abstract»

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  • Reducing the Positional Error of Connectivity-Based Positioning Algorithms Through Cooperation Between Neighbors

    Page(s): 1868 - 1882
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1550 KB) |  | HTML iconHTML  

    The information available to connectivity-based positioning algorithms is the radio range of sensor devices and the position estimates of neighbors and neighbors of neighbors. This information creates special graph theoretic structures which impose new constraints on the positions of sensor devices. The new constraints sometimes lead to a feasible set of positions with disconnected regions. These properties can be used to reduce the set of feasible positions for a node. In this paper, a new fully distributed positioning algorithm, called Orbit, which exploits these properties is presented for mobile sensor networks. The algorithm uses additional constraints and trims disconnected regions. These new constraints are generated through cooperation between neighbors. The performance of Orbit is examined for many communication and mobility models, including a probabilistic communication model generated from radio experiments. Computer simulation experiments demonstrate that Orbit outperforms a recently proposed positioning algorithm in terms of positional accuracy under different models with a wide range of parameter values. Orbit is implemented on resource limited sensor devices. This implementation demonstrates the feasibility of the algorithm for sensor devices. The algorithm is tested on deployments of the sensor devices in a field and the results are comparable to those from the simulation experiments. View full abstract»

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  • Throughput Optimization in Wireless Networks Under Stability and Packet Loss Constraints

    Page(s): 1883 - 1895
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    The problem of throughput optimization in decentralized wireless networks with spatial randomness under queue stability and packet loss constraints is investigated in this paper. Two key performance measures are analyzed, namely the effective link throughput and the network spatial throughput. Specifically, the tuple of medium access probability, coding rate, and maximum number of retransmissions that maximize each throughput metric is analytically derived for a class of Poisson networks, in which packets arrive at the transmitters following a geometrical distribution. Necessary conditions so that the effective link throughput and the network spatial throughput are stable and achievable under bounded packet loss are determined, as well as upper bounds for both cases by considering the unconstrained optimization problem. Our results show in which system configuration stable achievable throughput can be obtained as a function of the network density and the arrival rate. They also evince conditions for which the per-link throughput-maximizing operating points coincide or not with the aggregate network throughput-maximizing operating regime. View full abstract»

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  • Work-Conserving In-Sequence Striping in Multi-Band Wireless Backhaul Systems

    Page(s): 1896 - 1908
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    Link aggregation, or multi-band striping, has been used in wireless backhaul systems to overcome the limitations of bandwidth and transmission range. Work-conserving and in-sequence delivery are essential but conflicting requirements in multi-band striping systems. Previous schemes can achieve one or the other, but not both. The heterogeneous channel and time varying data rate in multi-band wireless backhaul systems present additional challenges. We aim at designing a multi-band striping algorithm to achieve both work-conserving and in-sequence delivery in the heterogeneous time-varying multi-band wireless backhaul system. We propose a parallel processing architecture for multi-band aggregation, and derive the necessary conditions for such system to achieve sequence preserving and work conserving. An optimum set of timing controls is developed and proved to provide the best performance. We design a work-conserving in-sequence striping algorithm and prove it to be sequence preserving and work conserving. The algorithm is then extended to practical data granularity. Performance analysis and simulation results demonstrate that our designs are able to preserve data sequence, reduce delay, and achieve 100% channel utilization. View full abstract»

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  • Open Access

    Page(s): 1909
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    Freely Available from IEEE
  • Rock Stars of Cybersecurity Conference

    Page(s): 1910
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    Freely Available from IEEE

Aims & Scope

Mobile Computing, as proposed in this Transactions, focuses on the key technical issues related to (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Prasant Mohapatra
Interim Vice-Provost and CIO
Professor, Dept. Computer Science
University of California, Davis, USA
pmohapatra@ucdavis.edu