Basem Shihada

King Abdullah University of Science and Technology, Djidda, Makkah, Saudi Arabia

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Publications (69)44.68 Total impact

  • Journal of Network and Computer Applications 08/2015; DOI:10.1016/j.jnca.2015.08.006 · 2.23 Impact Factor
  • Source
    Amr Elrasad · Basem Shihada ·

    IEEE International Conference on High Performance Switching and Routing (HPSR); 07/2015
  • Source
    Amr Elrasad · Basem Shihada ·
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    ABSTRACT: This work investigates void filling (idle periods) in long-reach Ethernet passive optical networks. We focus on reducing grant delays and hence reducing the average packet delay. We introduce a novel approach called parallel void thread (PVT), which allocates bandwidth grants during voids baseless of bandwidth requests. We introduce three different grant sizing schemes for PVT, namely void extension, count controlled batch void filling, and size controlled batch void filling. The proposed approaches can be integrated with almost all of the previously reported dynamic bandwidth allocation schemes. Unlike other void filling schemes, PVT is less sensitive to the differential distance between optical network units and can work very well in the case of limited differential distances. We have analytically investigated the packet delay and derived a bound condition for PVT to outperform the other competitors. We support our work with extensive simulation study considering bursty traffic with long range dependence for both the single-class and differentiated services (DiffServ) scenarios. Numerical results show delay reduction up to 35% compared with the non-void filling scheme for the single-class scenario. For DiffServ traffic, PVT achieves delay reduction up to 80% for expedited forward traffic, 52% for assured forward traffic, and 56% for best effort traffic.
    Journal of Optical Communications and Networking 07/2015; 7(7):656-668. DOI:10.1364/JOCN.7.000656 · 2.06 Impact Factor
  • A.R. Alabbasi · B. Shihada ·
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    ABSTRACT: In this paper, an energy efficient cognitive radio system is proposed. The proposed design optimizes the secondary user transmission power and the sensing duration combined with soft-sensing information to minimize the energy per goodbit. Due to the non-convex nature of the problem we prove its pseudo-convexity to guarantee the optimal solution. Furthermore, a quantization scheme, that discretize the soft-sensing information, is proposed and analyzed to reduce the overload of the continuously adapted power. Numerical results show that the energy per goodbit performance of the proposed system outperforms the benchmark systems. The impact of the quantization levels and other system parameters is evaluated in the numerical results.
  • Abdulrahman Alabbasi · Zouheir Rezki · Basem Shihada ·
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    ABSTRACT: In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.
    IEEE Transactions on Wireless Communications 05/2015; 14(5):2455-2469. DOI:10.1109/TWC.2014.2387161 · 2.50 Impact Factor
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    Li Xia · Basem Shihada ·
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    ABSTRACT: This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Filially, we conduct some simulation experiments to demonstrate the main idea of this paper.
    European Journal of Operational Research 05/2015; 242(3):778-787. DOI:10.1016/j.ejor.2014.10.063 · 2.36 Impact Factor
  • Amr Elrasad · Basem Shihada ·

    International Conference on Computer Communications (INFOCOM) Student Workshop; 04/2015
  • M. Aslani · A. Showail · B. Shihada ·

    IEEE International Conference on High Performance Switching and Routing (HPSR); 01/2015
  • Ahmad Showail · K. Jamshaid · B. Shihada ·

  • N. Bouacida · A. Showail · B. Shihada ·

    IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob); 01/2015
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    Ismail Alqerm · basem shihada ·
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    ABSTRACT: Cognitive Radio (CR) is an intelligent Software Defined Radio (SDR) that is capable to alter its transmission parameters according to predefined objectives and wireless environment condition. Cognitive engine exploits optimization and machine learning techniques to perform radio parameters configuration. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance. The optimization relies on adapting radio transmission parameters to environment conditions using constrained optimization modeling called fitness functions in an iterative manner. These functions include minimizing power consumption, packet error rate (PER), delay and interference. On the other hand, maximizing throughput and spectral efficiency. Cross-layer optimization is exploited to access environmental parameters from all TCP/IP stack layers. AMOS uses Genetic Algorithm (GA) that is adaptive in terms of its parameters and objective weights as the vehicle of optimization. The proposed scheme has demonstrated quick response and efficiency in three different scenarios compared to other schemes. In addition, it demonstrate its capability to optimize the performance of other TCP/IP layers in addition to the physical layer.
    IEEE GlobeCome 2014; 12/2014
  • Ahmad Showail · K. Jamshaid · B. Shihada ·
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    ABSTRACT: In this paper, we analyze the impact of large, persistently-full buffers ('bufferbloat') on various network dynamics in IEEE 802.11n wireless networks. Bufferbloat has mostly been studied in the context of wired networks. We study the impact of bufferbloat on a variety of wireless network topologies, including wireless LAN (WLAN) and multi-hop wireless networks. Our results show that a single FTP transfer between two Linux wireless hosts can saturate the buffers in the network stack, leading to RTT delays exceeding 4.5 s in multi-hop configurations. We show that well-designed Aggregate MAC Protocol Data Unit (A-MPDU) MAC-layer frame aggregation can reduce RTT delays while simultaneously increasing network throughput. However, additional measures may still be required to meet the constraints of real-time flows (such as VoIP). Our experiments show that large buffers can deteriorate the fairness in rate allocation in parking lot based multi-hop networks.
    IEEE Wireless Communications and Networking Conference (WCNC); 11/2014
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    ABSTRACT: Reliable data transmission is a fundamental challenge in resource-constrained wireless sensor networks. In current implementations, a single bit error requires retransmitting the entire frame. This incurs extra processing overhead and power consumption, especially for large frames. Frame fragmentation into small blocks with individual error detection codes can reduce the unnecessary retransmission of the correctly received blocks. The optimal block size, however, varies based on the wireless channel conditions. In this paper, we propose an interference-aware frame fragmentation scheme called iFrag. iFrag dynamically adjusts the number of blocks inside a frame based on current channel conditions, and effectively addresses all challenges associated with such dynamic partitioning. Through analytical and experimental results, we show that iFrag achieves up to improvement in goodput when the channel is noisy, while reducing the delay by 12 % compared to other static fragmentation approaches. On average, it shows a 13 % gain in goodput across all channel conditions used in our experiments. Our testbed results also show that iFrag lowers the energy consumed per useful bit by 60 %, as improved data transmission reliability reduces the number of frame retransmissions which increases the motes energy efficiency.
    Wireless Networks 10/2014; 20(7):1-18. DOI:10.1007/s11276-014-0722-1 · 0.96 Impact Factor
  • Abdulrahman Alabbasi · Zouheir Rezki · Basem Shihada ·
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    ABSTRACT: In this paper, we consider a cognitive radio multi-input–multi-output environment, in which we adapt our beamformer to maximize both energy efficiency (EE) and signal-to-interference-plus-noise ratio (SINR) metrics. Our design considers an underlaying communication using adaptive beamforming schemes combined with sensing information to achieve optimal energy-efficient systems. The proposed schemes maximize EE and SINR metrics subject to cognitive radio and quality-of-service constraints. The analysis of the proposed schemes is classified into two categories based on knowledge of the secondary-transmitter-to-primary-receiver channel. Since the optimizations of EE and SINR problems are not convex problems, we transform them into a standard semidefinite programming (SDP) form to guarantee that the optimal solutions are global. An analytical solution is provided for one scheme, while the second scheme is left in a standard SDP form. Selected numerical results are used to quantify the impact of the sensing information on the proposed schemes compared to the benchmark ones.
    IEEE Transactions on Wireless Communications 09/2014; 13(9):5095-5106. DOI:10.1109/TWC.2014.2323962 · 2.50 Impact Factor
  • Ahmad Showail · Kamran Jamshaid · Basem Shihada ·
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    ABSTRACT: Choosing the right buffer size in Wi-Fi networks is challenging due to the dynamic nature of the wireless environment. Over buffering or 'bufferbloat' may produce unacceptable end-to-end delays, while static small buffers may limit the performance gains that can be achieved with various 802.11n enhancements, such as frame aggregation. We propose WQM, a queue management scheme customized for wireless networks. WQM adapts the buffer size based on measured link characteristics and network load. Furthermore, it accounts for aggregate length when deciding about the optimal buffer size. We implement WQM on Linux and evaluate it on a wireless testbed. WQM reduces the end-to-end delay by up to 8x compared to Linux default buffer size, and 2x compared to CoDel, the state-of-the-art bufferbloat solution, while achieving comparable network goodput. Further, WQM improves fairness as it limits the ability of a single flow to saturate the buffer.
  • A.R. Dhaini · P.-H. Ho · Gangxiang Shen · Basem Shihada ·
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    ABSTRACT: Next-generation passive optical network (PON) has been considered in the past few years as a cost-effective broadband access technology. With the ever-increasing power saving concern, energy efficiency has been an important issue in its operations. In this paper, we propose a novel sleep-time sizing and scheduling framework for the implementation of green bandwidth allocation (GBA) in TDMA-PONs. The proposed framework leverages the batch-mode transmission feature of GBA to minimize the overhead due to frequent ONU on–off transitions. The optimal sleeping time sequence of each ONU is determined in every cycle without violating the maximum delay requirement. With multiple ONUs possibly accessing the shared media simultaneously, a collision may occur. To address this problem, we propose a new sleep-time sizing mechanism, namely Sort-And-Shift (SAS), in which the ONUs are sorted according to their expected transmission start times, and their sleep times are shifted to resolve any possible collision while ensuring maximum energy saving. Results show the effectiveness of the proposed framework and highlight the merits of our solutions .
    IEEE/ACM Transactions on Networking 06/2014; 22(3):850-863. DOI:10.1109/TNET.2013.2259596 · 1.81 Impact Factor
  • AbdulRahman Alabbasi · Zouheir Rezki · Basem Shihada ·
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    ABSTRACT: In this paper we consider a cognitive radio multi-input multi-output environment in which we adapt our beamformer to maximize both energy efficiency and signal to interference plus noise ratio (SINR) metrics. Our design considers an underlaying communication using adaptive beamforming schemes combined with the sensing information to achieve an optimal energy efficient system. The proposed schemes maximize the energy efficiency and SINR metrics subject to cognitive radio and quality of service constraints. Since the optimization of energy efficiency problem is not a convex problem, we transform it into a standard semi-definite programming (SDP) form to guarantee a global optimal solution. Analytical solution is provided for one scheme, while the other scheme is left in a standard SDP form. Selected numerical results are used to quantify the impact of the sensing information on the proposed schemes compared to the benchmark ones.
    2014 IEEE International Symposium on Information Theory (ISIT); 06/2014
  • Source
    Ismail Alqerm · Basem Shihada ·
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    ABSTRACT: Radio resource management becomes an important aspect of the current wireless networks because of spectrum scarcity and applications heterogeneity. Cognitive radio is a potential candidate for resource management because of its capability to satisfy the growing wireless demand and improve network efficiency. Decision-making is the main function of the radio resources management process as it determines the radio parameters that control the use of these resources. In this paper, we propose an adaptive decision-making scheme (ADMS) for radio resources management of different types of network applications including: power consuming, emergency, multimedia, and spectrum sharing. ADMS exploits genetic algorithm (GA) as an optimization tool for decision-making. It consists of the several objective functions for the decision-making process such as minimizing power consumption, packet error rate (PER), delay, and interference. On the other hand, maximizing throughput and spectral efficiency. Simulation results and test bed evaluation demonstrate ADMS functionality and efficiency.
    2014 IEEE 28th International Conference on Advanced Information Networking and Applications (AINA); 05/2014
  • Kamran Jamshaid · Basem Shihada · Ahmad Showail · Philip Levis ·
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    ABSTRACT: We analyze the problem of buffer sizing for backlogged TCP flows in 802.11-based wireless mesh networks. Our objective is to maintain high network utilization while providing low queueing delays. Unlike wired networks where a single link buffer feeds a bottleneck link, the radio spectral resource in a mesh network is shared among a set of contending mesh routers. We account for this by formulating the buffer size problem as sizing a collective buffer distributed over a set of interfering nodes. In this paper we propose mechanisms for sizing and distributing this collective buffer among the mesh nodes constituting the network bottleneck. Our mechanism factors in the network topology and wireless link rates, improving on pre-set buffer allocations that cannot optimally work across the range of configurations achievable with 802.11 radios. We evaluate our mechanisms using simulations as well as experiments on a testbed. Our results show that we can reduce the RTT of a flow by 6×6× or more, at the cost of less than 10% drop in end-to-end flow throughput.
    Ad Hoc Networks 05/2014; 16. DOI:10.1016/j.adhoc.2014.01.002 · 1.53 Impact Factor
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    ABSTRACT: Leak and backflow detection are essential aspects of Water Distribution System (WDS) monitoring. Most existing solutions for leak/backflow detection in WDSs focus on the placement of expensive static sensors located strategically. In contrast to these, we propose a solution whereby mobile sensors (i.e., their movement aided only by the inherent water flow in the system) detect leaks/backflow. Information about the leaks/backflow is collected from the sensors either by physically capturing them, or through wireless communication. Specifically, we propose models to maximize leak/backflow detection given a cost constraint (a limit on the number of sensors). Through extensive simulations, we demonstrate the superior performance of our proposed solution when compared with the state of the art solutions (e.g., algorithms/protocols and analysis).
    2014 IEEE 28th International Conference on Advanced Information Networking and Applications (AINA); 05/2014

Publication Stats

197 Citations
44.68 Total Impact Points


  • 2011-2015
    • King Abdullah University of Science and Technology
      • • Department of Electrical Engineering
      • • Department of Computer Science
      Djidda, Makkah, Saudi Arabia
  • 2013
    • University of Michigan
      Ann Arbor, Michigan, United States
  • 2010
    • Stanford University
      • Department of Computer Science
      Palo Alto, California, United States
  • 2005-2008
    • University of Waterloo
      • Department of Electrical & Computer Engineering
      Waterloo, Ontario, Canada