Using mobility and exception handling to achieve mobile agents that survive server crash failures

Mobile agent technology, when designed and used effectively, can minimize bandwidth consumption and autonomously provide a snapshot of the current context of a distributed system. Protecting mobile agents from server crashes is a challenging issue, since developers normally have no control over remote servers. Server crash failures can leave replicas, instable storage, unavailable for an unknown time period. Furthermore, few systems have considered the need for using a fault tolerant protocol among a group of collaborating mobile agents. This thesis uses exception handling to protect mobile agents from server crash failures. An exception model is proposed for mobile agents and two exception handler designs are investigated. The first exists at the server that created the mobile agent and uses a timeout mechanism. The second, the mobile shadow scheme, migrates with the mobile agent and operates at the previous server visited by the mobile agent. A case study application has been developed to compare the performance of the two exception handler designs. Performance results demonstrate that although the second design is slower it offers the smaller trip time when handling a server crash. Furthermore, no modification of the server environment is necessary. This thesis shows that the mobile shadow exception handling scheme reduces complexity for a group of mobile agents to survive server crashes. The scheme deploys a replica that monitors the server occupied by the master, at each stage of the itinerary. The replica exists at the previous server visited in the itinerary. Consequently, each group member is a single fault tolerant entity with respect to server crash failures. Other schemes introduce greater complexity and performance overheads since, for each stage of the itinerary, a group of replicas is sent to servers that offer an equivalent service. In addition, future research is established for fault tolerance in groups of collaborating mobile agents

Robust and cheating-resilient power auctioning on Resource Constrained Smart Micro-Grids

The principle of Continuous Double Auctioning (CDA) is known to provide an efficient way of matching supply and demand among distributed selfish participants with limited information. However, the literature indicates that the classic CDA algorithms developed for grid-like applications are centralised and insensitive to the processing resources capacity, which poses a hindrance for their application on resource constrained, smart micro-grids (RCSMG). A RCSMG loosely describes a micro-grid with distributed generators and demand controlled by selfish participants with limited information, power storage capacity and low literacy, communicate over an unreliable infrastructure burdened by limited bandwidth and low computational power of devices. In this thesis, we design and evaluate a CDA algorithm for power allocation in a RCSMG. Specifically, we offer the following contributions towards power auctioning on RCSMGs. First, we extend the original CDA scheme to enable decentralised auctioning. We do this by integrating a token-based, mutual-exclusion (MUTEX) distributive primitive, that ensures the CDA operates at a reasonably efficient time and message complexity of O(N) and O(logN) respectively, per critical section invocation (auction market execution). Our CDA algorithm scales better and avoids the single point of failure problem associated with centralised CDAs (which could be used to adversarially provoke a break-down of the grid marketing mechanism). In addition, the decentralised approach in our algorithm can help eliminate privacy and security concerns associated with centralised CDAs. Second, to handle CDA performance issues due to malfunctioning devices on an unreliable network (such as a lossy network), we extend our proposed CDA scheme to ensure robustness to failure. Using node redundancy, we modify the MUTEX protocol supporting our CDA algorithm to handle fail-stop and some Byzantine type faults of sites. This yields a time complexity of O(N), where N is number of cluster-head nodes; and message complexity of O((logN)+W) time, where W is the number of check-pointing messages. These results indicate that it is possible to add fault tolerance to a decentralised CDA, which guarantees continued participation in the auction while retaining reasonable performance overheads. In addition, we propose a decentralised consumption scheduling scheme that complements the auctioning scheme in guaranteeing successful power allocation within the RCSMG. Third, since grid participants are self-interested we must consider the issue of power theft that is provoked when participants cheat. We propose threat models centred on cheating attacks aimed at foiling the extended CDA scheme. More specifically, we focus on the Victim Strategy Downgrade; Collusion by Dynamic Strategy Change, Profiling with Market Prediction; and Strategy Manipulation cheating attacks, which are carried out by internal adversaries (auction participants). Internal adversaries are participants who want to get more benefits but have no interest in provoking a breakdown of the grid. However, their behaviour is dangerous because it could result in a breakdown of the grid. Fourth, to mitigate these cheating attacks, we propose an exception handling (EH) scheme, where sentinel agents use allocative efficiency and message overheads to detect and mitigate cheating forms. Sentinel agents are tasked to monitor trading agents to detect cheating and reprimand the misbehaving participant. Overall, message complexity expected in light demand is O(nLogN). The detection and resolution algorithm is expected to run in linear time complexity O(M). Overall, the main aim of our study is achieved by designing a resilient and cheating-free CDA algorithm that is scalable and performs well on resource constrained micro-grids. With the growing popularity of the CDA and its resource allocation applications, specifically to low resourced micro-grids, this thesis highlights further avenues for future research. First, we intend to extend the decentralised CDA algorithm to allow for participants’ mobile phones to connect (reconnect) at different shared smart meters. Such mobility should guarantee the desired CDA properties, the reliability and adequate security. Secondly, we seek to develop a simulation of the decentralised CDA based on the formal proofs presented in this thesis. Such a simulation platform can be used for future studies that involve decentralised CDAs. Third, we seek to find an optimal and efficient way in which the decentralised CDA and the scheduling algorithm can be integrated and deployed in a low resourced, smart micro-grid. Such an integration is important for system developers interested in exploiting the benefits of the two schemes while maintaining system efficiency. Forth, we aim to improve on the cheating detection and mitigation mechanism by developing an intrusion tolerance protocol. Such a scheme will allow continued auctioning in the presence of cheating attacks while incurring low performance overheads for applicability in a RCSMG

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.Siirretty Doriast

Edge Computing for Internet of Things

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond

Asynchronous approach in the plane: A deterministic polynomial algorithm

In this paper we study the task of approach of two mobile agents having the same limited range of vision and moving asynchronously in the plane. This task consists in getting them in finite time within each other's range of vision. The agents execute the same deterministic algorithm and are assumed to have a compass showing the cardinal directions as well as a unit measure. On the other hand, they do not share any global coordinates system (like GPS), cannot communicate and have distinct labels. Each agent knows its label but does not know the label of the other agent or the initial position of the other agent relative to its own. The route of an agent is a sequence of segments that are subsequently traversed in order to achieve approach. For each agent, the computation of its route depends only on its algorithm and its label. An adversary chooses the initial positions of both agents in the plane and controls the way each of them moves along every segment of the routes, in particular by arbitrarily varying the speeds of the agents. A deterministic approach algorithm is a deterministic algorithm that always allows two agents with any distinct labels to solve the task of approach regardless of the choices and the behavior of the adversary. The cost of a complete execution of an approach algorithm is the length of both parts of route travelled by the agents until approach is completed. Let $\Delta$ and $l$ be the initial distance separating the agents and the length of the shortest label, respectively. Assuming that $\Delta$ and $l$ are unknown to both agents, does there exist a deterministic approach algorithm always working at a cost that is polynomial in $\Delta$ and $l$? In this paper, we provide a positive answer to the above question by designing such an algorithm

Predicting and Recovering Link Failure Localization Using Competitive Swarm Optimization for DSR Protocol in MANET

Portable impromptu organization is a self-putting together, major construction-less, independent remote versatile hub that exists without even a trace of a determined base station or government association. MANET requires no extraordinary foundation as the organization is unique. Multicasting is an urgent issue in correspondence organizations. Multicast is one of the effective methods in MANET. In multicasting, information parcels from one hub are communicated to a bunch of recipient hubs all at once, at a similar time. In this research work, Failure Node Detection and Efficient Node Localization in a MANET situation are proposed. Localization in MANET is a main area that attracts significant research interest. Localization is a method to determine the nodes’ location in the communication network. A novel routing algorithm, which is used for Predicting and Recovering Link Failure Localization using a Genetic Algorithm with Competitive Swarm Optimization (PRLFL-GACSO) Algorithm is proposed in this study to calculate and recover link failure in MANET. The process of link failure detection is accomplished using mathematical modelling of the genetic algorithm and the routing is attained using the Competitive Swarm optimization technique. The result proposed MANET method makes use of the CSO algorithm, which facilitates a well-organized packet transfer from the source node to the destination node and enhances DSR routing performance. Based on node movement, link value, and endwise delay, the optimal route is found. The main benefit of the PRLFL-GACSO Algorithm is it achieves multiple optimal solutions over global information. Further, premature convergence is avoided using Competitive Swarm Optimization (CSO). The suggested work is measured based on the Ns simulator. The presentation metrix are PDR, endwise delay, power consumption, hit ratio, etc. The presentation of the proposed method is almost 4% and 5% greater than the present TEA-MDRP, RSTA-AOMDV, and RMQS-ua methods. After, the suggested method attains greater performance for detecting and recovering link failure. In future work, the hybrid multiway routing protocols are presented to provide link failure and route breakages and liability tolerance at the time of node failure, and it also increases the worth of service aspects, respectively

A cluster based communication architecture for distributed applications in mobile ad hoc networks

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2006Includes bibliographical references (leaves: 63-69)Text in English; Abstract: Turkish and Englishx, 85 leavesIn this thesis, we aim to design and implement three protocols on a hierarchical architecture to solve the balanced clustering, backbone formation and distributed mutual exclusion problems for mobile ad hoc network(MANET)s. Our ¯rst goal is to cluster the MANET into balanced partitions. Clustering is a widely used approach to ease implemen-tation of various problems such as routing and resource management in MANETs. We propose the Merging Clustering Algorithm(MCA) for clustering in MANETs that merges clusters to form higher level of clusters by increasing their levels. Secondly, we aim to con-struct a directed ring topology across clusterheads which were selected by MCA. Lastly, we implement the distributed mutual exclusion algorithm based on Ricart-Agrawala algo-rithm for MANETs(Mobile RA). Each cluster is represented by a coordinator node on the ring which implements distributed mutual exclusion algorithm on behalf of any member in the cluster it represents. We show the operations of the algorithms, analyze their time and message complexities and provide results in the simulation environment of ns2

Aika: A Distributed Edge System For Machine Learning Inference. Detecting and defending against abnormal behavior in untrusted edge environments

The edge computing paradigm has recently started to gain a lot of momentum. The field of Artificial Intelligence (AI) has also grown in recent years, and there is currently ongoing research that investigates how AI can be applied to numerous of different fields. This includes the edge computing domain. In Norway, there is currently ongoing research being conducted that investigates how the confluence between AI and edge computing can be used to hinder fish crime, by stationing surveillance equipment aboard fishing vessels, and perform all the monitoring directly on the vessel with support of AI. This is challenging for several reasons. First and foremost, the equipment needs to be stationed on the vessel, where actors may impose a threat to it and attempt to damage it, or interfere with the analytical process. The second challenge is to enable multiple machine learning pipelines to be executed effectively on the equipment. This requires a versatile computation model, where data is handled in a privacy preserving manner. This thesis presents Áika, a distributed edge computing system that supports machine learning inference in such untrusted edge environments. Áika is designed as a hierarchical fault tolerant system that supports a directed acyclic graph (DAG) computation model for executing machine inference on the edge, where a monitor residing in a trusted location can ensure that the system is running as expected. The experiment results demonstrate that Áika can tolerate failures while remaining operable with a stable throughput, although this will depend on the specific configuration and what computations that are implemented. The results also demonstrate that Áika can be used for both simple tasks, like counting words in a textual document, and for more complex tasks, like performing feature extraction using pre-trained deep learning models that are distributed across different workers. With Áika, application developers can develop fault tolerant and different distributed DAGs composed of multiple pipelines

Unified Role Assignment Framework For Wireless Sensor Networks

Wireless sensor networks are made possible by the continuing improvements in embedded sensor, VLSI, and wireless radio technologies. Currently, one of the important challenges in sensor networks is the design of a systematic network management framework that allows localized and collaborative resource control uniformly across all application services such as sensing, monitoring, tracking, data aggregation, and routing. The research in wireless sensor networks is currently oriented toward a cross-layer network abstraction that supports appropriate fine or course grained resource controls for energy efficiency. In that regard, we have designed a unified role-based service paradigm for wireless sensor networks. We pursue this by first developing a Role-based Hierarchical Self-Organization (RBSHO) protocol that organizes a connected dominating set (CDS) of nodes called dominators. This is done by hierarchically selecting nodes that possess cumulatively high energy, connectivity, and sensing capabilities in their local neighborhood. The RBHSO protocol then assigns specific tasks such as sensing, coordination, and routing to appropriate dominators that end up playing a certain role in the network. Roles, though abstract and implicit, expose role-specific resource controls by way of role assignment and scheduling. Based on this concept, we have designed a Unified Role-Assignment Framework (URAF) to model application services as roles played by local in-network sensor nodes with sensor capabilities used as rules for role identification. The URAF abstracts domain specific role attributes by three models: the role energy model, the role execution time model, and the role service utility model. The framework then generalizes resource management for services by providing abstractions for controlling the composition of a service in terms of roles, its assignment, reassignment, and scheduling. To the best of our knowledge, a generic role-based framework that provides a simple and unified network management solution for wireless sensor networks has not been proposed previously