ijece-140502292114050229212924CMV Verlagkhoffmann@cmv-verlag.comCMV VerlagNashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iranijece168237459302018162M.MohajerM. Taghizadeh Firoozjaee93020189110010.66224/ijece.28325.16.2.91http://ijece.org/fa/Article/28325http://ijece.org/fa/Article/Download/28325http://ijece.org/fa/Article/Download/28325http://ijece.org/fa/Article/Download/28325http://ijece.org/fa/Article/Download/28325http://ijece.org/fa/Article/Download/28325http://ijece.org/fa/Article/Download/28325http://ijece.org/fa/Article/Download/28325[1] C. H. Yu, K. Chung, D. Kim, and L. S. Kim, "An energy-efficient mobile vertex processor with multithread expanded VLIW architecture and vertex caches," IEEE J. of Solid-State Circuits, vol. 42, no. 10, pp. 2257-2269, Oct. 2007. [2] B. Nicolescu, N. Lgnat, Y. Savaria, and G. Nicolescu, "Analysis of real-time systems sensitivity to transient faults using MicroC kernel," IEEE Trans. Nuclear Science, vol. 53, no. 4, pp. 1902-1909, Aug. 2006. [3] A. B. Kahng and S. Kang, "Accuracy-configurable adder for approximate arithmetic designs," in Proc. 49th Annual Design Automation Conf., DAC'12, pp. 820-825, San Francisco, CA, USA, 3-7 Jun. 2012. [4] S. Venkataramani, S. T. Chakradhar, K. Roy, and A. Raghunathan, "Computing approximately, and efficiently," in Proc. Design, Automation & Test in Europe Conf., DATE'15, pp. 748-751, Grenoble, France, 9-13 Mar. 2015. [5] IEEE Computer Society (2008), IEEE standard for floating-point arithmetic, IEEE Standard 754-2008. [6] J. Ying, F. Tong, D. Nagle, and R. A. Rutenbar, "Reducing power by optimizing the necessary precision/range of floating-point arithmetic," IEEE Trans. VLSI Systems, vol. 8, no. 3, pp. 273-286, Jun. 2000. [7] I. Z. Milovanovic, E. I. Milovanovic, M. K. Stojcev, and M. P. Bekakos, "Orthogonal fault-tolerant systolic arrays for matrix multiplication," Microelectronics Reliability, vol. 51, no. 3, pp. 711-725, Mar. 2011. [8] M. Fazeli, A. Namazi, S. G. Miremadi, and A. Haghdoost, "Operand width aware hardware reuse: a low cost fault-tolerant approach to ALU design in embedded processors," Microelectronics Reliability, vol. 51, no. 12, pp. 2374-2387, Dec. 2011. [9] P. Reviriego, S. Z. Can, C. Eryılmaz, J. A. Maestro, and O. Ergin, "Exploiting processor features to implement error detection in reduced precision matrix multiplications," Microprocessors and Microsystems, vol. 38, no. 6, pp. 581-584, Aug. 2014. [10] A. Mukherjee and A. S. Dhar, "Real-time fault-tolerance with hot-standby topology for conditional sum adder," Microelectronics Reliability, vol. 55, no. 3-4, pp. 704-712, Feb./Mar. 2015. [11] M. Valinataj, "Fault-tolerant carry look-ahead adder architectures robust to multiple simultaneous errors," Microelectronics Reliability, vol. 55, no. 12, pp. 2845-2857, Dec. 2015. [12] D. Lipetz and E. Schwarz, "Self checking in current floating-point units," in Proc. 20th IEEE Symp. Computer Arithmetic, pp. 73-76, Tubingen, Germany, 25-27 Jul. 2011. [13] M. Maniatakos, Y. Makris, P. Kudva, and B. Fleischer, "Exponent monitoring for low-cost concurrent error detection in FPU control logic," in Proc. 29th IEEE VLSI Test Symp., pp. 235-240, Dana Point, CA, USA, 1-5 May 2011. [14] A. Gupta, et al., "Low power probabilistic floating point multiplier design," in Proc. IEEE Computer Society Annual Symp. VLSI, ISVLSI'11, pp. 182-187, Chennai, India, 4-6 Jul. 2011. [15] H. Zhang, W. Zhang, and J. Lach, "A low-power accuracy-configurable floating point multiplier," in Proc. 32nd IEEE Intl. Conf. Computer Design, ICCD'14, pp. 48-54, Seoul, South Korea, 19-22 Oct. 2014. [16] S. Hashemi, R. Iris Bahar, and S. Reda., "DRUM: a dynamic range unbiased multiplier for approximate applications," in Proc. IEEE Int. Conf. on Comp. Aided Design, ICCAD'15, pp. 418-425, Austin, TX, USA, 2-6 Nov. 2015. [17] S. Narayanamoorthy, H. Asghari Moghaddam, Z. Liu, T. Park, and N. Sung Kim, "Energy-efficient approximate multiplication for digital signal processing and classification applications," IEEE Trans. on VLSI, vol. 23, no. 6, pp. 1180-1184, Jun. 2015. [18] V. Camus, J. Schlachter, C. Enz, M. Gautschi, and F. K. Gurkaynak, "Approximate 32-bit floating-point unit design with 53% power-area product reduction," in Proc. 42nd European Solid-State Circuits Conf., ESSCIRC'16, pp. 465-468, Lausanne, Switzerland, 12-15 Sept. 2016. [19] M. Imani, D. Peroni, and T. Rosing, "CFPU: configurable floating point multiplier for energy-efficient computing," in Proc. 54th ACM/EDAC/IEEE Design Automation Conf., DAC'17, 6 pp., Austin, TX, USA, 18-22 Jun. 2017. [20] P. Yin, C. Wang, W. Liu, and F. Lombardi, "Design and performance evaluation of approximate floating-point multipliers," in Proc. IEEE Computer Society Annual Symp. VLSI, ISVLSI'16, pp. 296-301, Pittsburgh, PA, USA, 11-13 Jul. 2016. [21] A. Sunny, B. K. Mathew, and P. B. Dhanusha, "Area efficient high speed approximate multiplier with carry predictor," Procedia Technology, vol. 24, pp. 1170-1177, 2016. [22] M. Fathi and H. Nikmehr, "Improving accuracy, area and speed of approximate floating point multiplication using carry prediction," J. of Information Systems and Telecommunication, vol. 5, no. 2, pp. 120-127, Apr./Jun. 2017. [23] C. Liu, J. Han, and F. Lombardi, "A low-power, high-performance approximate multiplier with configurable partial error recovery," in Proc. Design, Automation & Test in Europe Conf., DATE'14, 4 pp. , Dresden, Germany, 24-28 Mar. 2014. [24] P. Yin, C. Wang, W. Liu, E. E. Swartzlander Jr., and F. Lombardi, "Designs of approximate floating-point multipliers with variable accuracy for error-tolerant applications," J. of Signal Processing Systems, vol. 90, no. 4, pp. 641-654, Apr. 2018. [25] P. J. Eibl, A. D. Cook, and D. J. Sorin, "Reduced precision checking for a floating point adder," in Proc. 24th IEEE Int. Symp. Defect and Fault Tolerance in VLSI Systems, pp. 145-152, Chicago, IL, USA, 7-9 Oct. 2009. [26] K. Seetharam, L. C. T. Keh, R. Nathan, and D. J. Sorin, "Applying reduced precision arithmetic to detect errors in floating point multiplication," in Proc. IEEE Pacific Rim Intl. Symp. Dependable Computing, PRDC'13, pp. 232-235, Vancouver, BC, Canada, 2-4 Dec. 2013. [27] M. Mohajer and M. Valinataj, "A novel reduced-precision fault-tolerant floating-point multiplier," Int. J. of Modern Education and Computer Science, vol. 9, no. 6, pp. 17-24, Jun. 2017. [28] B. Parhami, Computer Arithmetic, Algorithms and Hardware Designs, 2nd Ed., Oxford University Press, 2009.A.nourollahN.Behzadpour930201810111010.66224/ijece.28326.16.2.101http://ijece.org/fa/Article/28326http://ijece.org/fa/Article/Download/28326http://ijece.org/fa/Article/Download/28326http://ijece.org/fa/Article/Download/28326http://ijece.org/fa/Article/Download/28326http://ijece.org/fa/Article/Download/28326http://ijece.org/fa/Article/Download/28326http://ijece.org/fa/Article/Download/28326[1] J. E. Goodman, J. O'Rourke, and L. Guibas, Modeling Motion, pp. 1114-1132, 2004. [2] M. Fowler, Domain Specific Languages, Addison-Wesley Professional, 1st Ed., 2010. [3] J. P. Tolvanen and S. Kelly, "Metaedit+: defining and using integrated domain-specific modeling languages," in Proc. of the 24th ACM SIGPLAN Conf. Companion on Object Oriented Programming Systems Languages and Applications, OOPSLA'09, pp. 819-820, New York, NY, USA, 25-29 Oct. 2009. [4] A. Nordmann, N. Hochgeschwender, and S. Wrede, A Survey on Domain-Specific Languages in Robotics, pp. 195-206, Cham: Springer International Publishing, 2014. [5] R. Ryman-Kane, RhondaHughes Ryman, Benesh for Ballet, 1 Ed., 2014. [6] B. M. Farnell, Movement Notation Systems, Oxford, 1996. [7] O. Teitelbaum, et al., "Eshkol-Wachman movement notation in diagnosis: the early detection of asperger's syndrome," in Proc. of the National Academy of Sciences, United States of America, vol. 10132, pp. 11909-11914, 28 Jul. 2004. [8] A. Nordmann, N. Hochgeschwender, D. L. Wigand, and S. Wrede, "A survey on domain-specific modeling and languages in robotics," J. of Software Engineering in Robotics, vol. 7, no. 1, pp. 75-99, 2016. [9] E. D. Demaine and J. O'Rourke, Part I. Linkages, Cambridge University Press Cambridge, 2007. [10] R. Connelly and E. D. Demaine, Geometry and Topology of Polygonal Linkages, pp. 213-235, 2004. [11] S. Schneider, N. Hochgeschwender, and G. K. Kraetzschmar, "Declarative specification of task-based grasping with constraint validation," in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 919-926, Chicago, IL, USA, 14-18 Sep. 2014. [12] D. Vanthienen, M. Klotzbucher, J. D. Schutter, T. D. Laet, and H. Bruyninckx, "Rapid application development of constrained-based task modelling and execution using domain specific languages," in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 1860-1866, Tokyo, Japan, 3-7 Nov. 2013. [13] M. Frigerio, J. Buchli, and D. G. Caldwell, "Code generation of algebraic quantities for robot controllers," in Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 2346-2351, Vilamoura, Portugal, 7-12 Oct. 2012. [14] A. Nordmann, S. Wrede, and J. Steil, "Modeling of movement control architectures based on motion primitives using domain-specific languages," in Proc. IEEE Int. Conf. on Robotics and Automation, ICRA'15, pp. 5032-5039, Seattle, WA, USA, 26-30 May 2015. [15] G. Borghesan, E. Scioni, A. Kheddar, and H. Bruyninckx, "Introducing geometric constraint expressions into robot constrained motion specification and control," IEEE Robotics and Automation Letters, vol. 1, no. 2, pp. 1140-1147, Jul. 2016.H.DavoudiM.Rasti930201811112010.66224/ijece.28327.16.2.111http://ijece.org/fa/Article/28327http://ijece.org/fa/Article/Download/28327http://ijece.org/fa/Article/Download/28327http://ijece.org/fa/Article/Download/28327http://ijece.org/fa/Article/Download/28327http://ijece.org/fa/Article/Download/28327http://ijece.org/fa/Article/Download/28327http://ijece.org/fa/Article/Download/28327[1] R. Wang, H. Hu, and X. Yang, "Potentials and challenges of C-RAN supporting multi-RATs toward 5G mobile networks," IEEE Access vol. 2, pp. 1187-1195, 2014. [2] A. Abdelnasser and E. Hossain, "Two-tier OFDMA cellular cloud-RAN: joint resource allocation and admission control," in Proc. IEEE Global Communications Conf., GLOBECOM’15, 7 pp., San Diego, CA, USA, 6-10 Dec. 2015. [3] M. Adedoyin and O. Falowo, "Self-organizing radio resource management for next generation heterogeneous wireless networks," in Proc. IEEE Int. Conf. on Communications. ICC’16, 6 pp., Kuala Lumpur, Malaysia, 22-27 May 2016. [4] A. Checko, et al., "Cloud RAN for mobile networks-a technology overview," IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 405-426, Firstquarter 2015. [5] E. Dahlman, G. Mildh, S. Parkvall, J. Peisa, J. Sachs, and Y. Seln, "5G radio access," Ericsson Review, Jun. 2014. [6] V. Chandrasekhar and J. G. Andrews, "Femtocell networks: a survey," IEEE Commun. Mag., vol. 46, no. 9, pp. 59-67, Sep. 2008. [7] D. Fooladivanda and R. Catherine, "Joint resource allocation and user association for heterogeneous wireless cellular networks," IEEE Trans. on Wireless Communications, vol. 12, no. 1, pp. 248-257, Jan. 2013. [8] M. Peng, Y. Li, J. Jiang, J. Li, and C. Wang, "Heterogeneous cloud radio access networks: a new perspective for enhancing spectral and energy efficiencies," IEEE Wireless Communications, vol. 21, no. 6, pp. 126-135, Dec. 2014. [9] J. Kim and C. D. Ho, "A joint power and subchannel allocation scheme maximizing system capacity in indoor dense mobile communication systems," IEEE Trans. on Vehicular Technology, vol. 59, no. 9, pp. 4340-4353, Nov. 2010. [10] V. N. Ha and B. L. Long, "Fair resource allocation for OFDMA femtocell networks with macrocell protection," IEEE Trans. on Vehicular Technology, vol. 63, no. 3, pp. 1388-1401, Mar. 2014. [11] A. Abdelnasser, E. Hossain, and D. Kim, "Clustering and resource allocation for dense femtocells in a two-tier cellular OFDMA network," IEEE Trans. on Wireless Communications, vol. 13, no. 3, pp. 1628-1641, Mar. 2014. [12] H. Zhang, C. Jiang, N. C. Beaulieu, X. Chu, X. Wen, and M. Tao, "Resource allocation in spectrum-sharing OFDMA femtocells with heterogeneous services," IEEE Trans. on Communications, vol. 62, no. 7, pp. 2366-2377, Jul. 2014. [13] Y. Xu, Y. Hu, Q. Chen, R. Chai, and G. Li, "Distributed resource allocation for cognitive HetNets with cross-tier interference constraint," in Proc. IEEE Wireless Communications and Networking Conf., WCNC’17, 6 pp., San Francisco, CA, USA, 19-22 Mar. 2017. [14] L. Giupponi and C. Ibars, "Distributed interference control in ofdmabased femtocells," in Proc. 21st Annual IEEE Int. Symp. on Personal, Indoor and Mobile Radio Communications PIMRC’10, pp. 1201-1206, Instanbul, Turkey, 26-30 Sept. 2010. [15] N. Lu, Y. Jiang, F. Zheng, and X. You, "Energy efficient power control for the two-tier networks with small cells and massive MIMO," in Proc. Wireless Communications and Networking Conf. WCNC’16, pp. 127-132, Doha, Qatar, 3-6 Apr. 2016. [16] D. T. Ngo, S. Khakurel, and T. Le-Ngoc, "Joint subchannel assignment and power allocation for OFDMA femtocell networks," IEEE Trans. on Wireless Communications, vol. 13, no. 1, pp. 342-355, Jan. 2014. [17] A. Abdelnasser, E. Hossain, and D. Kim, "Tier-aware resource allocation in ofdma macrocell-small cell networks," IEEE Trans. on Communications, vol. 63, no. 3, pp. 695-710, Mar. 2015. [18] W. L. Winston, Operations Research: Applications and Algorithms, Cengage Learning, 2003. [19] A. Abdelnasser and E. Hossain, "Resource allocation for an OFDMA cloud-RAN of small cells overlaying a macrocell," IEEE Trans. on Mobile Computing, vol. 15, no. 11, pp. 2837-2850, Nov. 2016. [20] R. Byers, "A bisection method for measuring the distance of a stable matrix to the unstable matrices," SIAM J. on Scientific and Statistical Computing, vol. 9, no. 5, pp. 875-881, 1988. [21] K. Seong, M. Mohseni, and J. Cioffi, "Optimal resource allocation for OFDMA downlink systems," in Proc. IEEE Int. Symp. on Information Theory, pp. 1394-1398, Seattle, WA, USA, 9-14 Jul. 2006. [22] S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge, U. K.: Cambridge Univ. Press, 2004. [23] D. W. K. Ng and R. Schober, "Resource allocation and scheduling in multi-cell ofdma systems with decode-and-forward relaying," IEEE Trans. Wireless Communications, vol. 10, no. 7, pp. 2246-2258, Jul. 2011.MohammadKalantariS.SohrabiH.Rashidy KananH.Karami930201812113010.66224/ijece.28328.16.2.121http://ijece.org/fa/Article/28328http://ijece.org/fa/Article/Download/28328http://ijece.org/fa/Article/Download/28328http://ijece.org/fa/Article/Download/28328http://ijece.org/fa/Article/Download/28328http://ijece.org/fa/Article/Download/28328http://ijece.org/fa/Article/Download/28328http://ijece.org/fa/Article/Download/28328[1] X. S. Yang, Nature-Inspired Metaheuristic Algorithms, Luniver Press, 2010. [2] S. A. Ahmadi, "Human behavior-based optimization: a novel metaheuristic approach to solve complex optimization problems," Neural Computing and Applications, vol. 28, no. 1, pp. 233-244, Dec. 2017. [3] A. H. Gandomi, A. H. Alavi, and S. Talatahari, "Structural optimization using krill herd algorithm," Swarm Intelligence and Bio-Inspired Computation: Theory and Applications, pp. 335-349, 2013. [4] R. Nallakumar, N. Sengottaiyan, and K. S. Priya, "A survey on scheduling and the attributes of task scheduling in the cloud," Int. J. Adv. Res. Comput. Commun. Eng., vol. 3, no. 10, pp. 8167-8171, Oct. 2014. [5] C. W. Tsai and J. J. Rodrigues, "Metaheuristic scheduling for cloud: a survey," IEEE Systems J., vol. 8, no. 1, pp. 279-291, Mar. 2014. [6] F. Dong, J. Luo, L. Gao, and L. Ge, "A grid task scheduling algorithm based on QoS priority grouping," in Proc. 5th Int. Conf on Grid and Cooperative Computing, GCC’06, pp. 58-61, Hunan, China, 21-23 Oct. 2006. [7] U. Parlitz and L. Junge, "Synchronization of chaotic systems," in Proc. European Control Conf., ECC’99, pp. 4637-4642, Karlsruhe, Germany, 31 Aug.-3 Sept. 1999. [8] D. Yang, G. Li, and G. Cheng, "On the efficiency of chaos optimization algorithms for global optimization," Chaos, Solitons & Fractals, vol. 34, no. 4, pp. 1366-1375, Nov. 2007. [9] B. Alatas, "Chaotic harmony search algorithms," Applied Mathematics and Computation, vol. 216, no. 9, pp. 2687-2699, Jul. 2010. [10] A. H. Gandomi, G. J. Yun, X. S. Yang, and S. Talatahari, "Chaos-enhanced accelerated particle swarm optimization," Communications in Nonlinear Science and Numerical Simulation, vol. 18, no. 2, pp. 327-340, Feb. 2013. [11] B. Alatas, "Chaotic bee colony algorithms for global numerical optimization," Expert Systems with Applications, vol. 37, no. 8, pp. 5682-5687, Aug. 2010. [12] A. H. Gandomi and X. S. Yang, "Chaotic bat algorithm," J. of Computational Science, vol. 5, no. 2, pp. 224-232, Mar. 2014. [13] H. Karami, M. J. Sanjari, and G. B. Gharehpetian, "Hyper-spherical search (HSS) algorithm: a novel meta-heuristic algorithm to optimize nonlinear functions," Neural Computing and Applications, vol. 25, no. 6, pp. 1455-1465, Nov. 2014. [14] P. Arena, R. Caponetto, L. Fortuna, A. Rizzo, and M. La Rosa, "Self-organization in nonrecurrent complex systems," International J. of Bifurcation and Chaos, vol. 10, no. 5, pp. 1115-1125, May 2000. [15] B. Alatas, E. Akin, and A. B. Ozer, "Chaos embedded particle swarm optimization algorithms," Chaos, Solitons & Fractals, vol. 40, no. 4, pp. 1715-1734, May 2009. [16] E. N. Lorenz, "Deterministic nonperiodic flow," J. of the Atmospheric Sciences, vol. 20, no. 2, pp. 130-141, Mar. 1963. [17] L. Dos Santos Coelho and V. C. Mariani, "Use of chaotic sequences in a biologically inspired algorithm for engineering design optimization," Expert Systems with Applications, vol. 34, no. 3, pp. 1905-1913, Apr. 2008. [18] S. Das and P. N. Suganthan, Problem Definitions and Evaluation Criteria for CEC 2011 Competition on Testing Evolutionary Algorithms on Real World Optimization Problems, Technical Report, Dec. 2010.M.Davoodabadi FarahaniN.Mozayani930201813114110.66224/ijece.28329.16.2.131http://ijece.org/fa/Article/28329http://ijece.org/fa/Article/Download/28329http://ijece.org/fa/Article/Download/28329http://ijece.org/fa/Article/Download/28329http://ijece.org/fa/Article/Download/28329http://ijece.org/fa/Article/Download/28329http://ijece.org/fa/Article/Download/28329http://ijece.org/fa/Article/Download/28329[1] A. G. Barto and S. Mahadevan, "Recent advances in hierarchical reinforcement learning," Discrete Event Dynamic Systems, vol. 13, no. 4, pp. 341-379, Jan. 2003. [2] R. S. Sutton and A. G. Barto, "Reinforcement learning: an introduction," IEEE Trans. on Neural Networks, vol. 9, no. 5, pp. 1054-1054, Sep. 1998. [3] W. Moerman, Hierarchical Reinforcement Learning: Assignment of Behaviours to Subpolicies by Self-Organization, Ph.D Thesis, Cognitive Artificial Intelligence, Utrecht University, 2009. [4] J. Pfau, Plans as a Means for Guiding Reinforcement Learner, Master Thesis, Department of Information Systems, University of Melbourn, 2008. [5] T. Mann and S. Mannor, "Scaling up approximate value iteration with options: better policies with fewer iterations," in Proc. of the 31st Int. Conf. on Machine Learning, vol. 1, pp. 127-137, Beijing, China, 21-26 Jun. 2014. [6] A. McGovern and R. S. Sutton, Macro-Actions in Reinforcement Learning: An Empirical Analysis, University of Massachusetts, Department of Computer Science, Tech. Rep, pp. 98-70, 1998. [7] N. K. Jong, T. Hester, and P. Stone, "The utility of temporal abstraction in reinforcement learning," in Proc. of the 7th Int. Joint Conf. on Autonomous Agents and Multiagent Systems, vol. 1, pp. 299-306, Estoril, Portugal, 12-16 May 2008. [8] R. S. Sutton, D. Precup, and S. Singh, "Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning," Artificial Intelligence, vol. 112, no. 1-2, pp. 181-211, Aug. 1999. [9] T. Dietterich, "An overview of MAXQ hierarchical reinforcement learning," Abstraction, Reformulation, and Approximation, pp. 26-44, 2000. [10] M. Stolle, Automated Discovery of Options in Reinforcement Learning, M.Sc Thesis, McGill University, 2004. [11] A. McGovern and A. G. Barto, "Automatic discovery of subgoals in reinforcement learning using diverse density," in Proc. Int. Workshop Conf. Machine Learning, pp. 361-368, 28 Jun-1 Jul. 2001. [12] S. Mannor, I. Menache, A. Hoze, and U. Klein, "Dynamic abstraction in reinforcement learning via clustering," in Proc. of the 21st Int. Conf. on Machine Learning, p. 71, Banff, Alberta, Canada, 4-8 Jul. 2004. [13] O. Simsek and A. Barto, "Identifying useful subgoals in reinforcement learning by local graph partitioning," in Proc. of the 22nd Int. Conf. on Machine Learning, pp. 816-823, Bonn, Germany, 7-11 Aug. 2005. [14] A. Jonsson and A. Barto, "A causal approach to hierarchical decomposition of factored MDPs," in Proc. of the 22nd Int. Conf. on Machine Learning, pp. 401-408, Bonn, Germany, 7-11 Aug. 2005. [15] N. Mehta, S. Ray, P. Tadepalli, and T. Dietterich, "Automatic discovery and transfer of MAXQ hierarchies," in Proc. of the 25th Int. Conf. on Machine Learning, pp. 648-655, Helsinki, Finland, 5-9 Jul. 2008. [16] P. Zang, P. Zhou, D. Minnen, and C. Isbell, "Discovering options from example trajectories," in Proc. of the 26th Annual Int. Conf. on Machine Learning, pp. 1217-1224, Montreal, Quebec, Canada, 14-18 Jun. 2009. [17] I. Menache, S. Mannor, and N. Shimkin, "Q-cut-dynamic discovery of sub-goals in reinforcement learning," in Proc. 13th European Conf. on Machine Learning, ECML'02, pp. 187-195, 19-23 Aug. 2002. [18] O. Simsek, Behavioral Building Blocks for Autonomous Agents: Description, Identification, and Learning, Ph.D. Thesis, Department of Computer Science, University of Massachusetts Amherst, 2008. [19] V. Mathew, K. Peeyush, and B. Ravindran, "Abstraction in reinforcement learning in terms of metastability," in Proc. of the 10th European Workshop on Reinforcement Learning, EWRL'12, pp. 1-14, 2012. [20] C. C. Chiu and V. W. Soo, "Automatic complexity reduction in reinforcement learning," Computational Intelligence, vol. 26, no. 1, pp. 1-25, Feb. 2010. [21] J. H. Metzen and F. Kirchner, "Incremental learning of skill collections based on intrinsic motivation," Frontiers in Neurorobotics, vol. 7, p. 11, Jan. 2013. [22] P. Bacon and D. Precup, "Using label propagation for learning temporally abstract actions in reinforcement learning," in Proc. of the Workshop on Multiagent Interaction Networks, pp. 357-368, 2013. [23] M. Davoodabadi and H. Beigy, "A new method for discovering subgoals and constructing options in reinforcement learning," in Proc. IICAI, pp. 441-450, 2011. [24] O. Simsek and A. G. Barto, "Skill characterization based on betweenness," in Proc. 21th Int. Conf. on Neural Information Processing Systems, NIPS'08, pp. p.1497-1504, Vancouver, Canada, 8-10 Dec. 2008. [25] A. A. Rad, M. Hasler, and P. Moradi, "Automatic skill acquisition in reinforcement learning using connection graph stability centrality," in Proc. of 2010 IEEE Int. Symp. on Circuits and Systems, ISCAS'10, pp. 697-700, Paris, France, 30 May-2 Jun. 2010. [26] L. J. Lin, "Self-improving reactive agents based on reinforcement learning, planning and teaching," Machine Learning, vol. 8, no. 3-4, pp. 293-321, May 1992. [27] R. S. Sutton, D. Precup, and S. Singh, "Intra-option learning about temporally abstract actions," in Proc. of the Fifteenth Int. Conf. on Machine Learning, pp. 556-564, 1998. [28] M. E. J. Newman and M. Girvan, "Finding and evaluating community structure in networks," Physical Review E, vol. 69, no. 2, p. 026113, Feb. 2004. [29] U. N. Raghavan, R. Albert, and S. Kumara, "Near linear time algorithm to detect community structures in large-scale networks," Physical Review E, vol. 76, no. 3, p. 036106, Sep. 2007. [30] M. E. J. Newman, "Fast algorithm for detecting community structure in networks," Physical Review E, vol. 69, no. 6, p. 066133, Jun. 2004. [31] K. Merrick, Modelling Motivation for Experience-Based Attention Focus in Reinforcement Learning, Ph.D. Thesis, School of Information Technologies, the University of Sydney, 2007. [32] M. Davoodabadi and N. Mozayani, "Automatic construction and evaluation of options in reinforcement learning," Submitted in Artificial Intelligence, https://www.journals.elsevier.com/artificial-intelligence/ [33] A. G. Barto, S. Singh, and N. Chentanez, "Intrinsically motivated learning of hierarchical collections of skills," in Proc. of the 3rd Int. Conf. on Development and Learning, ICDL’04, pp. 112-119, Salk Institute, San Diego, USA, Oct. 2004. [34] J. Murata, "Controlled use of subgoals in reinforcement learning," Robotics, Automation and Control, pp. 167-182, 2008.MohammadMollashahiM.MehrjooM.Abiri930201814214810.66224/ijece.28330.16.2.142http://ijece.org/fa/Article/28330http://ijece.org/fa/Article/Download/28330http://ijece.org/fa/Article/Download/28330http://ijece.org/fa/Article/Download/28330http://ijece.org/fa/Article/Download/28330http://ijece.org/fa/Article/Download/28330http://ijece.org/fa/Article/Download/28330http://ijece.org/fa/Article/Download/28330[1] V. Chandrasekhar, J. G. Andrews, and A. Gatherer, "Femtocell networks: a survey," IEEE Communications Magazine, vol. 46, no. 9, pp. 59-67, Sept. 2008. [2] D. Kim, H. Lee, and D. Hong, "A survey of in-band full-duplex transmission: from the perspective of PHY and MAC layers," IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2017-2046, Feb. 2015. [3] J. I. Choi, M. Jain, K. Srinivasan, P. Levis, and S. Katti, "Achieving single channel, full duplex wireless communication," in Proc. of the ACM 16th Annual Int. Conf. on Mobile Computing and Networking, 12 pp., Chicago, Illinois, USA, 20-24 Sept. 2010. [4] E. Aryafar, M. A. Khojastepour, K. Sundaresan, S. Rangarajan, and M. Chiang, "MIDU: enabling MIMO full duplex," in Proc. of the ACM 18th Annual Int. Conf. on Mobile Computing and Networking, pp. 257-268, Istanbul, Turkey, 22-26 Aug. 2012. [5] K. S. Munasinghe, I. Elgendi, A. Jamalipour, and D. Sharma, "Traffic offloading 3-tiered SDN architecture for denseNets," IEEE Network, vol. 31, no. 3, pp. 56-62, May 2017. [6] D. C. Oh, H. C. Lee, and Y. H. Lee, "Power control and beamforming for femtocells in the presence of channel uncertainty," IEEE Trans. on Vehicular Technology, vol. 60, no. 6, pp. 2545-2554, Jun. 2011. [7] T. M. Nguyen, T. Q. Queki, and H. Shin, "Opportunistic interference alignment in MIMO femtocell networks," in Proc. IEEE Int. Symp. on Information Theory Proc., ISIT’12, pp. 2631-2635, Cambridge, MA, USA, 1-6 Jul. 2012. [8] D. Zarbouti, G. Tsoulos, and G. Athanasiadou, "4G multicell systems with in-band full duplex relays: using beamforming to lower self-interference and/or transmitted powers," in Proc. IEEE 81st. Vehicular Technology Conf., VTC Spring’15, 6 pp., Glasgow, UK, 11-14 May 2015. [9] DUPLO, D4.1.1. Performance of Full-Duplex Systems, Jan. 2014. Available: http://www.fp7-duplo.eu/index.php/deliverables. [10] J. Michanan, R. Dewri, and M. J. Rutherford, "Understanding the power-performance tradeoff through Pareto analysis of live performance data," in Proc. IEEE Int. Green Computing Conf., IGCC’14, 8 pp., Dallas, TX, USA, 3-5 Nov. 2014.D.RahbariM.Nickray930201814915610.66224/ijece.28331.16.2.149http://ijece.org/fa/Article/28331http://ijece.org/fa/Article/Download/28331http://ijece.org/fa/Article/Download/28331http://ijece.org/fa/Article/Download/28331http://ijece.org/fa/Article/Download/28331http://ijece.org/fa/Article/Download/28331http://ijece.org/fa/Article/Download/28331http://ijece.org/fa/Article/Download/28331[1] H. Gupta, A. V. Dastjerdi, S. K. Ghosh, and R. Buyya, "IFogsim: a toolkit for modeling and simulation of resource management techniques in internet of things, edge and fog computing environments," Software: Practice and Experience, vol. 47, no. 9, pp. 1275-1296, Jun. 2017. [2] M. Aazam, M. St-Hilaire, C. H. Lung, and I. Lambadaris, "Pre-fog: Iot trace based probabilistic resource estimation at fog," in Proc. 13th IEEE Annual. Consumer Communications and Networking Conf., CCNC'16, pp. 12-17, Jan. 2016. [3] A. M. Rahmani, T. N. Gia, B. Negash, A. Anzanpour, I. Azimi, M. Jiang, and P. Liljeberg, "Exploiting smart e-health gateways at the edge of healthcare internet-of-things: a fog computing approach," Future Generation Computer Systems, vol. 78, no. 2, pp. 641-658, Feb. 2017. [4] M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies, "The case for vm-based cloudlets in mobile computing," IEEE Pervasive Computing, vol. 8, no. 4, pp. 14-23, Oct. 2009. [5] P. Gupta and S. P. Ghrera, "Trust and deadline aware scheduling algorithm for cloud infrastructure using ant colony optimization," in Proc. IEEE Int. Conf. on Innovation and Challenges in Cyber Security, ICICCS-INBUSH'16, pp. 187-191, Noida, India, 3-5 Feb. 2016. [6] M. A. Rodriguez and R. Buyya, "Deadline based resource provisioning and scheduling algorithm for scientific workflows on clouds," IEEE Trans. on Cloud Computing, vol. 2, no. 2, pp. 222-235, Apr. 2014. [7] J. Lv, X. Wang, M. Huang, H. Cheng, and F. Li, "Solving 0-1 knapsack problem by greedy degree and expectation efficiency," Applied Soft Computing, vol. 41, pp. 94-103, Apr. 2016. [8] M. Y. Cheng and D. Prayogo, "Symbiotic organisms search: a new metaheuristic optimization algorithm," Computers & Structures, vol. 139, vol. 139, pp. 98-112, Jul. 2014. [9] M. A. Rodriguez and R. Buyya, "A taxonomy and survey on scheduling algorithms for scientific workflows in iaas cloud computing environments," Concurrency and Computation: Practice and Experience, vol. 29, no. 8, pp. 1-23, Dec. 2017. [10] M. E. Frincu, S. Genaud, and J. Gossa, "Comparing provisioning and scheduling strategies for workflows on clouds," in Proc. IEEE 27th Int. Parallel and Distributed Processing Symp. Workshops and PhD Forum, IPDPSW'13, pp. 2101-2110, Cambridge, MA, USA, 20-24 May. 2013. [11] M. Malawski, K. Figiela, M. Bubak, E. Deelman, and J. Nabrzyski, "Scheduling multilevel deadline-constrained scientific workflows on clouds based on cost optimization," Scientific Programming, vol. 2015, pp. 1-13, Jan. 2015. [12] J. J. Durillo and R. Prodan, "Multi-objective workflow scheduling in amazon ec2," Cluster Computing, vol. 17, no. 2, pp. 169-189, Jun. 2014. [13] D. Poola, K. Ramamohanarao, and R. Buyya, "Fault-tolerant workflow scheduling using spot instances on clouds," Procedia Computer Science, vol. 29, pp. 523-533, Jun. 2014. [14] X. Zhu, J. Wang, H. Guo, D. Zhu, L. T. Yang, and L. Liu, "Fault-tolerant scheduling for real-time scientific workflows with elastic resource provisioning in virtualized clouds," IEEE Trans. on Parallel and Distributed Systems, vol. 27, no. 12, pp. 3501-3517, Mar. 2016. [15] L. F. Bittencourt, J. Diaz-Montes, R. Buyya, O. F. Rana, and M. Parashar, "Mobility-aware application scheduling in fog computing," IEEE Cloud Computing, vol. 4, no. 2, pp. 26-35, Apr. 2017. [16] X. Q. Pham and E. N. Huh, "Towards task scheduling in a cloud-fog computing system," in Proc. 18th Asia-Pacific IEEE Network Operations and Management Symp., APNOMS', 4 pp., Kanazawa, Japan, 5-7 Oct. 2016. [17] Y. Sun, T. Dang, and J. Zhou, "User scheduling and cluster formation in fog computing based radio access networks," in Proc. IEEE Int. Conf. on Ubiquitous Wireless Broadband ICUWB, 4 pp., Nanjing, China, 16-19 Oct. 2016. [18] X. Chen and L. Wang, "Exploring fog computing-based adaptive vehicular data scheduling policies through a compositional formal methodpepa," IEEE Communications Letters, vol. 21, no. 4, pp. 745-748, Jan. 2017. [19] H. E. Zahaf, A. E. H. Benyamina, R. Olejnik, and G. Lipari, "Energy efficient scheduling for moldable real-time tasks on heterogeneous computing platforms," J. of Systems Architecture, vol. 74, pp. 46-60, Mar. 2017. [20] S. Bitam, S. Zeadally, and A. Mellouk, "Fog computing job scheduling optimization based on bees swarm," Enterprise Information Systems, vol. vol. 12 no. 4, pp. 373-397, Apr. 2017. [21] T. Wang, X. Wei, C. Tang, and J. Fan, "Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints," Peer-to-Peer Networking and Applications, 11, no. 4, pp. 793-807, Jul. 2017. [22] F. Lao, X. Zhang, and Z. Guo, "Parallelizing video transcoding using map-reduce-based cloud computing," in Proc. IEEE Int.Symp.on Circuits and Systems, ISCAS'12, pp. 2905-2908, Seoul, South Korea, 20-23 May 2012. [23] M. A. Rodriguez and R. Buyya, "A responsive knapsack-based algorithm for resource provisioning and scheduling of scientific workflows in clouds," in Proc. 44th IEEE Int. Conf. on Parallel Processing, ICPP'15, pp. 839-848, Beijing, China, 1-4 Sept. 2015. [24] S. Rahim, et al., "Towards multiple knapsack problem approach for home energy management in smart grid," in Proc. 18th IEEE Int. Conf. on Network-Based Information Systems, NBiS'15, pp. 48-52, Taipei, Taiwan, 2-4 Sept. 2015. [25] S. Chen, J. Wu, and Z. Lu, "A cloud computing resource scheduling policy based on genetic algorithm with multiple fitness," in Proc. 12th IEEE Int. Conf. on Computer and Information Technology, CIT'12, pp. 177-184, Chengdu, China, 27-29 Oct. 2012. [26] Q. Ni, A. B. Garcia Hernando, and I. P. de la Cruz, "The elderlys independent living in smart homes: a characterization of activities and sensing infrastructure survey to facilitate services development," Sensors, vol. 15, no. 5, pp. 11312-11362, May 2015. [27] R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, and R. Buyya, "Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms," Software: Practice and Experience, vol. 41, no. 1, pp. 23-50, Aug. 2011.M.HabibiA.AhmadyfardH.hassanpour930201815716310.66224/ijece.28332.16.2.157http://ijece.org/fa/Article/28332http://ijece.org/fa/Article/Download/28332http://ijece.org/fa/Article/Download/28332http://ijece.org/fa/Article/Download/28332http://ijece.org/fa/Article/Download/28332http://ijece.org/fa/Article/Download/28332http://ijece.org/fa/Article/Download/28332http://ijece.org/fa/Article/Download/28332[1] M. Bevilacqua, A. Roumy, C. Guillemot, and M. Morel, "Single-image super-resolution via linear mapping of interpolated self-examples," IEEE Trans. on Image Processing, vol. 23, no. 12, pp. 5334-5347, Dec. 2014. [2] T. S. Huang and R. Y. Tsai, "Multiframe image restoration and registration," Advances in Computer Vision and Image Processing, vol. 1, no. 7, pp. 317-339, Apr. 1984. [3] M. Irani and S. Peleg, "Super resolution from image sequences," in Proc. 10th Int. Conf. on Pattern Recognition, vol. 2, pp. 115-120, Jun. 1990. [4] J. W. Hwang and H. S. Lee, "Adaptive image interpolation based on local gradient features," IEEE Signal Processing Letters, vol. 11, no. 3, pp. 359-362, Feb. 2004. [5] H. Quang Luong, A. Ledda, and W. Philips, "Non-local image interpolation," in Proc. IEEE Int. Conf. on Image Processing ICIP'06, pp. 693-696, Atlanta, GA, USA, 8-11 Oct. 2006. [6] Y. Cha and S. Kim, "Edge-forming methods for color image zooming," IEEE Trans. Image Processing, vol. 15, no. 8, pp. 2315-2323, Aug. 2006. [7] Y. Cha and S. Kim, "PDE-based interpolation for image super resolution," International Journal of Future Generation Communication and Networking, vol. 1, pp. 214-219, Dec. 2007. [8] H. Kim, Y. Cha, and S. Kim, "Curvature interpolation method for image zooming," IEEE Trans. on Image Processing, vol. 20, no. 7, pp. 1895-1903, Jul. 2011. [9] F. Malgouyres and F. Guichard, "Edge direction preserving image zooming: a mathematical and numerical analysis," SIAM J. on Numerical Analysis, vol. 39, no. 1, pp. 1-37, Nov. 2001. [10] A. Belahmidi and F. Guichard, "A partial differential equation approach to image zoom," in Proc. Int. Conf. on Image Processing, ICIP'04, pp. 649-652, Singapore, Singapore, 24-27 Oct. 2004. [11] S. G. Chang, Z. Cvetkovic, and M. Vetterli, "Locally adaptive wavelet-based image interpolation," IEEE Trans. on Image Processing, vol. 15, no. 6, pp. 1471-1485, Jun. 2006. [12] G. Freedman and R. Fattal, "Image and video upscaling from local self-examples," ACM Trans. on Graphics, vol. 28, no. 3, pp. 1-10, Apr. 2010. [13] J. Yang, Z. Lin, and S. Cohen, "Fast image super-resolution based on in-place example regression," in Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, CVPR'13, pp. 1059_1066, Portland, OR, USA, 23-28 Jun. 2013. [14] D. Glasner, S. Bagon, and M. Irani, "Super-resolution from a single image," in Proc. IEEE 12th Int. Conf. on Computer Vision, ICCV'09, pp. 349-356, Kyoto, Japan, 29 Sept.-2 Oct. 2009. [15] C. Y. Yang, J. B. Huang, and M. H. Yang, "Exploiting self-similarities for single frame super-resolution," in Proc. Asian Conf. on Computer Vision, ACCV'10, vol. 3, pp. 497-510, Queenstown, New Zealand, 8-12 Nov. 2010. [16] M. C. Yang, C. H. Wang, T. Y. Hu, and Y. C. F. Wang, "Learning context-aware sparse representation for single image super-resolution," in Proc. IEEE Int. Conf. on Image Processing, ICIP'11, pp. 1349-1352, Brussels, Belgium, 11-14 Sept. 2011. [17] W. T. Freeman, T. R. Jones, and E. C. Pasztor, "Example-based superresolution," IEEE Comput. Graph. Appl., vol. 22, no. 2, pp. 56-65, Apr. 2002. [18] H. Chang, D. Y. Yeung, and Y. Xiong, "Super-resolution through neighbor embedding," in Proc. IEEE Conf. Comput. Vision and Pattern Recognition, pp. 275-282, Washington, DC, USA, 27 Jun.-2 Jul. 2004. [19] N. Suetake, M. Sakano, and E. Uchino, "Image super-resolution based on local self-similarity," Optical Review, vol. 15, no. 11, pp. 26-30, Jan. 2008. [20] M. C. Yang and Y. C. F. Wang, "A self-learning approach to single image super-resolution," IEEE Trans. on Multimedia, vol. 15, no. 3, pp. 498-508, Apr. 2013. [21] J. Yang, J. Wright, T. S. Huang, and Y. Ma, "Image super-resolution as sparse representation of raw image patches," in Proc. IEEE Conf. Comput. Vision and Pattern Recognition, CVPR'08, pp. 2861-2873, Anchorage, AK, USA, 23-28 Jun. 2008. [22] J. Yang, J. Wright, T. Huang, and Y. Ma, "Image super-resolution via sparse representation," IEEE Trans. Image Process., vol. 19, no. 11, pp. 2861-2873, Nov. 2010. [23] M. C. Yang, C. T. Chu, and Y. C. F. Wang, "Learning sparse image representation with support vector regression for single-image super-resolution," in Proc. IEEE Int. Conf. Image Processing, ICIP'10, pp. 1973-1976, Hong Kong, China, 26-29 Sept. 2010. [24] K. I. Kim and Y. Kwon, "Single-image super-resolution using sparse regression and natural image prior," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 6, pp. 1127-1133, Jun. 2010. [25] M. Protter and M. Elad, "Image sequence denoising via sparse and redundant representations," IEEE Trans. Image Process., vol. 18, no. 1, pp. 27-35, Jan. 2009.