A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the referenced journal articl

A Systematic Approach to Constructing Families of Incremental Topology Control Algorithms Using Graph Transformation

In the communication systems domain, constructing and maintaining network topologies via topology control (TC) algorithms is an important cross-cutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of TC algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of TC algorithms. Furthermore, even though many TC algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of TC algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual TC algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; TC algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given TC algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of TC algorithms. To show the feasibility of our approach, we reneging six existing TC algorithms and develop e-kTC, a novel energy-efficient variant of the TC algorithm kTC. Finally, we evaluate a subset of the specified TC algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.Comment: Corresponds to the accepted manuscrip

A distributed knowledge-based approach to flexible automation : the contract-net framework

Includes bibliographical references (p. 26-29)

Self-organization and autonomy in computational networks: agents-based contractual workflow paradigm

We describe an agents-based contractual workflow paradigm for Self-organization and autonomy in computational networks. The agent-based paradigm can be interpreted as the outcome arising out of deterministic, nondeterministic or stochastic interaction among a set of agents that includes the environment. These interactions are like chemical reactions and result in self-organization. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of elements, so that the agents carry out the required actions. Also we describe the application of this paradigm in finding short duration paths, chemical- patent mining, and in cloud computing services

Correct-by-Construction Development of Dynamic Topology Control Algorithms

Wireless devices are influencing our everyday lives today and will even more so in the future. A wireless sensor network (WSN) consists of dozens to hundreds of small, cheap, battery-powered, resource-constrained sensor devices (motes) that cooperate to serve a common purpose. These networks are applied in safety- and security-critical areas (e.g., e-health, intrusion detection). The topology of such a system is an attributed graph consisting of nodes representing the devices and edges representing the communication links between devices. Topology control (TC) improves the energy consumption behavior of a WSN by blocking costly links. This allows a mote to reduce its transmission power. A TC algorithm must fulfill important consistency properties (e.g., that the resulting topology is connected). The traditional development process for TC algorithms only considers consistency properties during the initial specification phase. The actual implementation is carried out manually, which is error prone and time consuming. Thus, it is difficult to verify that the implementation fulfills the required consistency properties. The problem becomes even more severe if the development process is iterative. Additionally, many TC algorithms are batch algorithms, which process the entire topology, irrespective of the extent of the topology modifications since the last execution. Therefore, dynamic TC is desirable, which reacts to change events of the topology. In this thesis, we propose a model-driven correct-by-construction methodology for developing dynamic TC algorithms. We model local consistency properties using graph constraints and global consistency properties using second-order logic. Graph transformation rules capture the different types of topology modifications. To specify the control flow of a TC algorithm, we employ the programmed graph transformation language story-driven modeling. We presume that local consistency properties jointly imply the global consistency properties. We ensure the fulfillment of the local consistency properties by synthesizing weakest preconditions for each rule. The synthesized preconditions prohibit the application of a rule if and only if the application would lead to a violation of a consistency property. Still, this restriction is infeasible for topology modifications that need to be executed in any case. Therefore, as a major contribution of this thesis, we propose the anticipation loop synthesis algorithm, which transforms the synthesized preconditions into routines that anticipate all violations of these preconditions. This algorithm also enables the correct-by-construction runtime reconfiguration of adaptive WSNs. We provide tooling for both common evaluation steps. Cobolt allows to evaluate the specified TC algorithms rapidly using the network simulator Simonstrator. cMoflon generates embedded C code for hardware testbeds that build on the sensor operating system Contiki

Model Checking Paxos in Spin

We present a formal model of a distributed consensus algorithm in the executable specification language Promela extended with a new type of guards, called counting guards, needed to implement transitions that depend on majority voting. Our formalization exploits abstractions that follow from reduction theorems applied to the specific case-study. We apply the model checker Spin to automatically validate finite instances of the model and to extract preconditions on the size of quorums used in the election phases of the protocol.Comment: In Proceedings GandALF 2014, arXiv:1408.556

Diagnosis and Threat Detection Capabilities of the SERENITY Monitoring Framework

The SERENITY monitoring framework offers mechanisms for diagnosing the causes of violations of security and dependability (S&D) properties and detecting potential violations of such properties, called “threats”. Diagnostic information and threat detection are often necessary for deciding what an appropriate reaction to a violation is and taking pre-emptive actions against predicted violations, respectively. In this chapter, we describe the mechanisms of the SERENITY monitoring framework which generate diagnostic information for violations of S&D properties and detecting threats

Concurrent Systems Need Both Sequences And Serializers

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Office of Naval Research of the Department of Defense under contract N00014-75-C-0522.Contemporary concurrent programming languages fall roughly into two classes. Languages in the first class support the notion of a sequence of values and some kind of pipelining operation over the sequence of values. Languages in the second class support the notion of transactions and some way to serialize transactions. In terms of the actor model of computation this distinction corresponds to the difference between serialized and unserialized actors. In this paper the utility of modeling both serialized and unserialized actors in a coherent formalism is demonstrated.MIT Artificial Intelligence Laboratory Department of Defense Office of Naval Researc