Joint Source-Channel Coding of JPEG 2000 Image Transmission Over Two-Way Multi-Relay Networks

In this paper, we develop a two-way multi-relay scheme for JPEG 2000 image transmission. We adopt a modified time-division broadcast (TDBC) cooperative protocol, and derive its power allocation and relay selection under a fairness constraint. The symbol error probability of the optimal system configuration is then derived. After that, a joint source-channel coding (JSCC) problem is formulated to find the optimal number of JPEG 2000 quality layers for the image and the number of channel coding packets for each JPEG 2000 codeblock that can minimize the reconstructed image distortion for the two users, subject to a rate constraint. Two fast algorithms based on dynamic programming (DP) and branch and bound (BB) are then developed. Simulation demonstrates that the proposed JSCC scheme achieves better performance and lower complexity than other similar transmission systems

A program analysis framework for tccp based on abstract interpretation

[EN] The timed concurrent constraint language (tccp) is a timed extension of the concurrent constraint paradigm. tccp was defined to model reactive systems, where infinite behaviors arise naturally. In previous works, a semantic framework and abstract diagnosis method for the language have been defined. On the basis of that semantic framework, this paper proposes an abstract semantics that, together with a widening operator, is suitable for the definition of different analyses for tccp programs. The abstract semantics is correct and can be represented as a finite graph where each node represents a hypothetical (abstract) computational step of the program. The widening operator allows us to guarantee the convergence of the abstract fixpoint computation.This author has been supported by the Andalusian Excellence Project P11-TIC-7659. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under grants TIN 2015-69175-C4-1-R and TIN 2013-45732-C4-1-P and by Generalitat Valenciana PROMETEOII/2015/013Comini, M.; Gallardo, M.; Titolo, L.; Villanueva, A. (2017). A program analysis framework for tccp based on abstract interpretation. Formal Aspects of Computing. 29(3):531-557. https://doi.org/10.1007/s00165-016-0409-8S531557293Alpuente M, Gallardo MM, Pimentel E, Villanueva A (2006) A semantic framework for the abstract model checking of tccp programs. Theor Comput Scie 346(1): 58–95Bagnara R, Hill PM., Ricci E, Zaffanella E (2005) Precise widening operators for convex polyhedra. Sci Comput Program 58(1–2):28–56Cousot P, Cousot R (1977) Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints. In: Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on principles of programming languages, Los Angeles, California, January 17–19. ACM Press, New York, pp 238–252Clarke EM, Grumberg O, Jha S, Lu Y, Veith H (2000) Counterexample-guided abstraction refinement. In: CAV, Lecture Notes in Computer Science, vol 1855. Springer, pp 154–169Comini M, Gallardo MM, Titolo L, Villanueva A (2015) Abstract Analysis of Universal Properties for tccp. In: Falaschi M (ed) Logic-based Program Synthesis and Transformation, 25th International Symposium, LOPSTR 2015. Revised Selected Papers, Lecture Notes in Computer Science, vol 9527. Springer, pp 163–178Comini M, Titolo L, Villanueva A (2011) Abstract diagnosis for timed concurrent constraint programs. Theory Pract Logic Programm 11(4-5):487–502Comini M, Titolo L, Villanueva A (2013) A condensed goal-independent bottom-up fixpoint modeling the behavior of tccp. Technical report, DSIC, Universitat Politècnica de València. http://riunet.upv.es/handle/10251/34328de Boer FS, Gabbrielli M, Meo MC (2000) A timed concurrent constraint language. Inf Comput 161(1): 45–83Falaschi M, Gabbrielli M, Marriott K, Palamidessi C (1993) Compositional analysis for concurrent constraint programming. In: Proceedings of the eighth annual IEEE symposium on logic in computer science, Los Alamitos, CA, USA, IEEE Computer Society Press, pp 210–221Falaschi M, Olarte C, Palamidessi C (2015) Abstract interpretation of temporal concurrent constraint programs. Theory and Pract Logic Program (TPLP) 15(3): 312–357Falaschi M, Villanueva A (2006) Automatic verification of timed concurrent constraint programs. Theory Pract Logic Program 6(3): 265–300Gallardo MM, Merino P, Pimentel E (2002) Refinement of LTL formulas for abstract model checking. In: Static analysis, 9th international symposium, SAS 2002, Madrid, Spain, September 17–20, 2002, Proceedings, pp 395–410Saraswat VA (1993) Concurrent constraint programming. The MIT Press, CambridgeSaraswat VA, Rinard M, Panangaden P (1991) The semantic foundations of concurrent constraint programming. In: Proceedings of the 18th ACM SIGPLAN-SIGACT symposium on principles of programming languages. ACM, New York, pp 333–352Zaffanella E, Giacobazzi R, Levi G (1997) Abstracting synchronization in concurrent constraint programming. J Funct Logic Program (6

Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings

Constraint programming is a paradigm wherein relations between variables are stated in the form of constraints. Many real life problems come from uncertain and dynamic environments, where the initial constraints and domains may change during its execution. Thus, the solution found for the problem may become invalid. The search forrobustsolutions for constraint satisfaction problems (CSPs) has become an important issue in the ¿eld of constraint programming. In some cases, there exists knowledge about the uncertain and dynamic environment. In other cases, this information is unknown or hard to obtain. In this paper, we consider CSPs with discrete and ordered domains where changes only involve restrictions or expansions of domains or constraints. To this end, we model CSPs as weighted CSPs (WCSPs) by assigning weights to each valid tuple of the problem constraints and domains. The weight of each valid tuple is based on its distance from the borders of the space of valid tuples in the corresponding constraint/domain. This distance is estimated by a new concept introduced in this paper: coverings. Thus, the best solution for the modeled WCSP can be considered as a most robust solution for the original CSP according to these assumptionsThis work has been partially supported by the research projects TIN2010-20976-C02-01 (Min. de Ciencia e Innovacion, Spain) and P19/08 (Min. de Fomento, Spain-FEDER), and the fellowship program FPU.Climent Aunés, LI.; Wallace, RJ.; Salido Gregorio, MA.; Barber Sanchís, F. (2013). Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings. Artificial Intelligence Review. 1-26. https://doi.org/10.1007/s10462-013-9420-0S126Climent L, Salido M, Barber F (2011) Reformulating dynamic linear constraint satisfaction problems as weighted csps for searching robust solutions. 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