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Dynamic Resource Reallocation Between Deployment Components
"... Today’s software systems are becoming increasingly configurable and designed for deployment on a plethora of architectures, ranging from sequential machines via multicore and distributed architectures to the cloud. Examples of such systems are found in, e.g., software product lines, serviceoriente ..."
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Today’s software systems are becoming increasingly configurable and designed for deployment on a plethora of architectures, ranging from sequential machines via multicore and distributed architectures to the cloud. Examples of such systems are found in, e.g., software product lines, serviceoriented computing, information systems, embedded systems, operating systems, and telephony. To model and analyze systems without a fixed architecture, the models need to naturally capture and range over relevant deployment scenarios. For this purpose, it is interesting to lift aspects of lowlevel deployment concerns to the abstraction level of the modeling language. In this paper, the objectoriented modeling language Creol is extended with a notion of dynamic deployment components with parametric processing resources, such that processor resources may be explicitly reallocated. The approach is compositional in the sense that functional models and reallocation strategies are both expressed in Creol, and functional models can be run alone or in combination with different reallocation strategies. The formal semantics of deployment components is given in rewriting logic, extending the semantics of Creol, and executes on Maude, which allows simulations and test suites to be applied to models which vary in their available resources as well as in their resource reallocation strategies.
Grouping Nodes in Wireless Sensor Networks Using Coalitional Game Theory
 Proceedings of the 16th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS
, 2011
"... Abstract. Wireless sensor networks are typically adhoc networks of resourceconstrained nodes; in particular, the nodes are limited in power resources. It can be difficult and costly to replace sensor nodes, for instance when implanted in the human body. Data transmission is the major consumer of ..."
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Abstract. Wireless sensor networks are typically adhoc networks of resourceconstrained nodes; in particular, the nodes are limited in power resources. It can be difficult and costly to replace sensor nodes, for instance when implanted in the human body. Data transmission is the major consumer of power, so it is important to have powerefficient protocols. In order to reduce the total power consumption in the network, we consider nodes which cooperate to transmit data. Nodes which cooperate, form a group. A mobile node may at some point be without a group, in which case it is desirable for the node to be able to join a group. In this paper we propose a modification of the AODV protocol to decide whether a node should join a given group, using coalitional game theory to determine what is beneficial in terms of power consumption. The protocol is formalized in rewriting logic, implemented in the Maude tool, and validated by means of Maude's model exploration facilities.
Group selection by nodes in wireless sensor networks using coalitional game theory
 in: Proc. 16th Intl. Conf. on Engineering of Complex Computer Systems (ICECCS 2011), IEEE Computer
, 2011
"... Wireless sensor networks consist of resourceconstrained nodes; especially with respect to power resources. In many cases, the replacement of a dead node is difficult and costly, e.g. an implanted node in the human body. Our main goal in this paper is reducing the total power consumption of the netwo ..."
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Wireless sensor networks consist of resourceconstrained nodes; especially with respect to power resources. In many cases, the replacement of a dead node is difficult and costly, e.g. an implanted node in the human body. Our main goal in this paper is reducing the total power consumption of the network. For this purpose, we consider the cooperation of nodes in data transmission in terms of a group, since the major consumer of power is the data transmission process. A mobile node may move to a new location, in which it is desirable for the node to join a group. In this paper, we propose an algorithm for nodes to choose the best group in their signal range, using coalitional game theory to determine what is beneficial in terms of power consumption. The protocol is formalized in rewriting logic, implemented in the Maude tool, and validated by means of Maude’s model exploration facilities. Simulationbased tools are in general not able to prove the protocol. However, by using Maude, we prove the correctness of our proposed protocol, by searching for failures of the protocol, through all possible behaviors of sensors. These searches prove that grouping nodes is done correctly in all reachable states from a set of initial states of the model. In addition, we simulate our model in order to quantitatively analyze the efficiency of the proposed protocol. The results show significant improvements in power efficiency. 1.
P.C.: A probabilistic strategy language for probabilistic rewrite theories and its application to cloud computing
, 2012
"... Abstract. Several formal models combine probabilistic and nondeterministic features. To allow their probabilistic simulation and statistical model checking by means of pseudorandom number sampling, all sources of nondeterminism must first be quantified. However, current tools offer limited flexibi ..."
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Abstract. Several formal models combine probabilistic and nondeterministic features. To allow their probabilistic simulation and statistical model checking by means of pseudorandom number sampling, all sources of nondeterminism must first be quantified. However, current tools offer limited flexibility for the user to define how the nondeterminism should be quantified. In this paper, we propose an expressive probabilistic strategy language that allows the user to define complex strategies for quantifying the nondeterminism in probabilistic rewrite theories. We have implemented PSMaude, a tool that extends Maude with a probabilistic simulator and a statistical model checker for our language. We illustrate the convenience of being able to define different probabilistic strategies on top of a system by a cloud computing example, where different load balancing policies can be specified by different probabilistic strategies. We then use PSMaude to analyze the QoS provided by different policies.
Group Selection by Nodes in Wireless Sensor Networks Using Coalitional Game Theory
, 2011
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
A Probabilistic Strategy Language for Probabilistic Rewrite Theories and its Application to Cloud Computing
, 2014
"... Abstract. Several formal models combine probabilistic and nondeterministic features. To allow their probabilistic simulation and statistical model checking by means of pseudorandom number sampling, all sources of nondeterminism must first be quantified. However, current tools offer limited flexibi ..."
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Abstract. Several formal models combine probabilistic and nondeterministic features. To allow their probabilistic simulation and statistical model checking by means of pseudorandom number sampling, all sources of nondeterminism must first be quantified. However, current tools offer limited flexibility for the user to define how the nondeterminism should be quantified. In this report we propose an expressive probabilistic strategy language that allows the user to define complex strategies for quantifying the nondeterminism in probabilistic rewrite theories. These strategies may depend on the current system state, and their associated weight expressions can be given by any computable function defined equationally in Maude. We have implemented PSMaude, a tool that extends Maude with a probabilistic simulator and a statistical model checker for our language. We illustrate the convenience of being able to define different probabilistic strategies by a cloud computing example, where a (nonprobabilistic) rewrite theory defines the capabilities of the cloud computing infrastructure, and where different load balancing policies are specified by different probabilistic strategies. Our language also enables a Maudebased safety/QoS modeling and analysis methodology in which key safety properties can be verified for a basic “uncluttered ” nonprobabilistic model, and where QoS properties for different probabilistic strategies can be analyzed by probabilistic simulation and statistical model checking. 1
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS 1 Evolutionary and Principled Search St
"... Abstract—Interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown; finding optimal solutions is generally difficult. However, protocol tuning can yield significant gains in energy efficiency and resource requirements, which is of pa ..."
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Abstract—Interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown; finding optimal solutions is generally difficult. However, protocol tuning can yield significant gains in energy efficiency and resource requirements, which is of particular importance for sensornet systems in which resource availability is severely restricted. We address this multiobjective optimization problem for two dissimilar routing protocols and by two distinct approaches. First, we apply factorial design and statistical model fitting methods to reject insignificant factors and locate regions of the problem space containing nearoptimal solutions by principled search. Second, we apply the Strength Pareto Evolutionary Algorithm 2 and TwoArchive evolutionary algorithms to explore the problem space, with each iteration potentially yielding solutions of higher quality and diversity than the preceding iteration. Whereas a principled search methodology yields a generally applicable survey of the problem space and enables performance prediction, the evolutionary approach yields viable solutions of higher quality and at lower experimental cost. This is the first study in which sensornet protocol optimization has been explicitly formulated as a multiobjective problem and solved with stateoftheart multiobjective evolutionary algorithms. Index Terms—Evolutionary Algorithms (EAs), experiment design, multiobjective optimization, protocols, sensornets.
MULEbased Wireless Sensor Networks: Probabilistic Modeling and Quantitative Analysis
"... Abstract. Wireless sensor networks (WSNs) consist of resourceconstrained nodes; especially with respect to power. In most cases, the replacement of a dead node is difficult and costly. It is therefore crucial to minimize the total energy consumption of the network. Since the major consumer of power ..."
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Abstract. Wireless sensor networks (WSNs) consist of resourceconstrained nodes; especially with respect to power. In most cases, the replacement of a dead node is difficult and costly. It is therefore crucial to minimize the total energy consumption of the network. Since the major consumer of power in WSNs is the data transmission process, we consider nodes which cooperate for data transmission in terms of groups. A group has a leader which collects data from the members and communicates with the outside of the group. We propose and formalize a model for data collection in which mobile entities, called data MULEs, are used to move between group leaders and collect data messages using shortrange and lowpower data transmission. We combine declarative and operational modeling. The declarative model abstractly captures behavior without committing to specific transitions by means of probability distributions, whereas the operational model is given as a concrete transition system in rewriting logic. The probabilistic, declarative model is not used to select transition rules, but to stochastically capture the result of applying rules. Technically, we use probabilistic rewriting logic and embed our models into PMaude, which gives us a simulation engine for the combined models. We perform statistical quantitative analysis based on repeated discreteevent simulations in Maude. 1
Management Protocol for Wireless Sensor Networks
, 2008
"... A formal analysis of a key management protocol, called LEAP (Localized Encryption and Authentication Protocol), intended for wireless sensor networks is presented in this paper. LEAP is modeled using the high level formal language HLSPL and checked using the AVISPA tool for attacks on the security a ..."
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A formal analysis of a key management protocol, called LEAP (Localized Encryption and Authentication Protocol), intended for wireless sensor networks is presented in this paper. LEAP is modeled using the high level formal language HLSPL and checked using the AVISPA tool for attacks on the security and authenticity of the exchanges. We focus on the protocol’s establishment of pairwise keys for nearest neighbors and for multihop neighbors. We then use this foundation to test the protocol’s method of cluster key redistribution. Finally, we check LEAP’s use of µTESLA, an authentication protocol utilizing a oneway key chain and delayed key disclosure, which LEAP uses for authentication of node revocation messages. This work was supported by the National Science Foundation.
Creative Commons Attribution License. Model Checking Classes of Metric LTL Properties of ObjectOriented RealTime Maude Specifications
"... This paper presents a transformational approach for model checking two important classes of metric temporal logic (MTL) properties, namely, bounded response and minimum separation, for nonhierarchical objectoriented RealTime Maude specifications. We prove the correctness of our model checking al ..."
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This paper presents a transformational approach for model checking two important classes of metric temporal logic (MTL) properties, namely, bounded response and minimum separation, for nonhierarchical objectoriented RealTime Maude specifications. We prove the correctness of our model checking algorithms, which terminate under reasonable nonZenoness assumptions when the reachable state space is finite. These new model checking features have been integrated into RealTime Maude, and are used to analyze a network of medical devices and a 4way traffic intersection system. 1