Single and Group Agent Migration: Algorithms, Bounds, and Optimality Issues

Wireless sensor systems have drawn much attention from a considerable part of scientific community during the last years. The advances in this field range from the design of battery-powered embedded nodes to the development of software (i.e. operating system, middleware, etc) especially designed to run on such resource-constrained devices. One of the most challenging parts for both hardware and software oriented work is to maximize the lifetime of such nodes. This thesis focuses on the design and implementation of mobile code placement and migration algorithms for distributed applications in order to reduce the amount of application-level communication performed over the network. Since the largest part of a node’s energy expenditure is attributed to the wireless communication (not code execution), reducing the energy consumption becomes of paramount importance, leading in that way to an increased system lifetime. In the sequel, we give a brief overview of the application model, the algorithms and the middleware designed and implemented in the context of this thesis. The model adopted in this work is inspired by the POBICOS [91] platform, where the application is organized as a set of software entities (agents) that communicate with each other to implement the desired functionality. An agent can be ―non-generic? or ―generic?. Non-generic agents use special resources of a node, e.g. a sensor measuring a physical quantity or an actuator controlling a device or function. On the contrary, generic agents perform computational tasks and decision making at a higher level, without relying on special resources. Chapter 1 introduces the agent migration problem stated as follows: given an application that is deployed in a sensor network, perform generic agent migrations in order to reduce the data exchanged over the network due to the application-level communication between agents. We propose fully distributed algorithms that migrate an agent towards its center of gravity (in terms of communication load), thereby reducing the network cost. Also, two protocols are presented for handling the case of nodes with storage constraints (for hosting agents). iv Chapter 2 examines the same (above) problem, with the difference that it considers migrations of agent groups instead of single agent migrations. The algorithms in question deal with co-located agents that are ―mutually dependent?, which in the case of the simpler algorithms may hinder migration, leading to noticeably inferior placements. Chapter 3 discusses the competitiveness of the aforementioned algorithms versus the optimal algorithm. Also, it presents an enhancement of the group migration algorithms in order for them to produce an optimal agent placement (in terms of the network cost incurred by the application). It should be stressed that this enhancement guarantees optimality only if nodes do not have storage constraints, else the problem is NP-complete. Chapter 4 proposes fully distributed algorithms for the problem of generic agent migrations for resource-constrained nodes, introducing the concept of ―evictions?. Specifically, agent migrations are considered that are not beneficial in their own right but free space which can be used to perform additional (beneficial) migrations. Of course, the ultimate goal is to reduce the network load, so the total benefit of the migrations must be greater than the cost of the non-beneficial ones. In Chapter 5 we focus on the problem that the aforementioned algorithms are not able to ―guess? whether a (group) migration will turn out to actually reduce the network cost. They simply assume that the structure and communication pattern of the application remains stable for a ―sufficiently? long time, so as to amortize the migration cost. As a consequence, frequent changes in the application-level load may lead to frequent agent migrations, thereby increasing the network cost (instead of reducing it). For example, an agent may continuously ―oscillate? between two nodes due to periodic changes of the communication load with other agents (changing its center of gravity), before the respective migration cost is amortized. For this reason, we propose online algorithms, along with a discussion of their competitiveness versus the offline optimal algorithm. In Chapters 6 and 7 we propose centralized algorithms tackling more complex problems. Specifically, chapter 6 addresses the problem of reducing the network cost through migrations of both generic and non-generic agents, considering that the nodes of the system have storage capacity limitations. The proposed algorithms use graph coloring techniques. In Chapter 7, a two-dimensional problem is considered, the objectives being: (a) to maximize the number of agents hosted by the nodes of the system; and (b) to maximize the network lifetime (maximize the lifetime of the first node that depletes its battery). We propose algorithms solving each dimension (sequentially) in an independent way, along with a branch-and-bound algorithm v tackling the problem concurrently in both dimensions. Regarding the first dimension of the problem, a considerable part of the algorithms involves the de-fragmentation of the nodes’ storage capacity, through agent migrations. Chapter 8 describes the implementation of the component of the POBICOS middleware that provides full-fledged, distributed, agent management functionality, on top of the TinyOS embedded operating system. Specifically, we describe: i) the mechanism for creating agents on eligible nodes; ii) the mechanism for transporting agent-level messages; iii) the mechanism detecting and destroying ―orphan? agents; and iv) the mechanism for the migration of generic agents with full transparency for the application. Finally, Chapter 9 discusses works related to this thesis, while Chapter 10 includes an overview of this dissertation and future directions.

Profiling environmental parameter using a large number of spatially distributed wireless sensor network (WSN) NODEs is an extensive illustration of advanced modern technologies, but high power requirement for WSN NODEs limits the widespread deployment of these technologies. Currently, WSN NODEs are extensively powered up using batteries, but the battery has limitation of lifetime, power density, and environmental concerns. To overcome this issue, energy harvester (EH) is developed and presented in this paper. Solar-based EH has been identified as the most viable source of energy to be harvested for autonomous WSN NODEs. Besides, a novel chemical-based EH is reported as the potential secondary source for harvesting energy because of its uninterrupted availability. By integrating both solar-based EH and chemical-based EH, a hybrid energy harvester (HEH) is developed to power up WSN NODEs. Experimental results from the real-time deployment shows that, besides supporting the daily operation of WSN NODE and Router, the developed HEH is capable of producing a surplus of 971 mA·hr equivalent energy to be stored inside the storage for NODE and 528.24 mA·hr equivalent energy for Router, which is significantly enough for perpetual operation of autonomous WSN NODEs used in environmental parameter profiling.

Herein, an Internet of Things (IoT) system with remote reconfigurable wireless sensor network (WSN) nodes is presented and its application to measure group work activity in a classroom is discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), gateways, and remotely reconfigurable WSN Nodes. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

Trust and reputation systems have been regarded as a powerful tool to defend against insider attacks caused by the captured nodes in wireless sensor networks (WSNs). However, trust systems are vulnerable to on-off attacks, in which malicious nodes can opportunistically behave good or bad, compromising the network with the hope that bad behavior will be undetected. Thus, malicious nodes can remain trusted while behaving badly. In this paper, we propose O2Trust, On-Off attack mitigation for Trust systems in wireless sensor networks. O2Trust adopts the penalty policy against the misbehavior history of each node in the network as a reliable factor that should influence on the calculation of the trust value. This punishment future helps to perceive malicious node that aim to launch intelligent attacks against trust-establishment and consequently on-off attack is mitigated efficiently.

Nowadays, the efficiency of multiagent systems in wireless sensor networks prompts the researchers to use these emerging mobile software packets in different simulated approaches or real-world applications. Heterogeneous and distributed wireless sensor networks could be integrated with the multiagent systems to map the real-world challenges into the artificial intelligence world. The multiagent systems have been applied from simulated approaches like object detection/tracking, healthcare, control/assistant, and security systems to real-world applications, including medical/human-care systems and unmanned aerial vehicles. Furthermore, the integration of wireless sensor networks with multiagent systems have emerged novel application, which is known as mobile robots. However, the extensive use of mobile agents in wireless sensor networks has posed different challenges for researchers, including security, resource, and timing limitation. In this work, we review recent simulated approaches and real-world applications of multiagent systems in wireless sensor networks, in which a set of common factors about the things that have been studied are extracted and compared to analyze the performance of mobile agent–based systems in the wireless sensor networks, as well. This analysis provides new research directions about multiagent systems in wireless sensor networks for interested researchers. Finally, a novel framework for dealing with the challenges of multiagent-based applications in the wireless sensor networks which have been mentioned is suggested.

Over the past decades, many WSN (Wireless Sensor Network) systems have emerged. Today, the WSN systems with different technologies have started to become parts of Internet of Things (IoT) and Cyber-Physical Systems(CPSs). This situation has also led to the emergence of heterogeneous and autonomous WSN structures. In these types of complex projects, involving different WSN systems, it is necessary to well define the structure of WSN heterogeneity in order to perform some important operations such as interoperability and resource-sharing. To this end, the paper presents a WSN heterogeneity classification model. In the classification, WSN heterogeneity is addressed from a general perspective. The classification considers not only the heterogeneity within a WSN but also the heterogeneity which can be occurred in the scope of IoT/CPS projects. As far as is known, this type of classification on WSN heterogeneity has been proposed for the first time in literature.

Automatic delivery and recovery system of Wireless Sensor Networks (WSN) nodes based on UAV for agricultural applications

The increasing interest of researchers in service oriented architecture (SOA) for wireless sensor networks (WSNs) is opening new unexplored venues in the field of WSNs. In service oriented systems, services are configured and composed of various other services and thus perform complex tasks. In such composite services, the geospatial locations of services and their coverage is of vital importance as they signify the geospatial relevance of the service to the area of interest to the user. In this paper, we present a service-oriented system for WSNs that is capable of performing service configuration under geospatial and relevancy constraints. We present and evaluate "Cost Based Model (CBM)" and "Gain Based Model (GBM)" approaches to capture the relevancy of services hosted on WSN nodes in composite service configuration. The system is resilient to failures and can operate in manual or autonomous recovery modes. The system supports three service configuration methods namely, distributed, centralized and hybrid. Furthermore, we present a novel emulation mechanism for testing the performance of our proposed relevancy models and show that our system efficiently configures services.

Over the last few years, security concern has a very important role over the wireless sensor networks (WSNs). There are lot of attacks on WSN due to its open deployment and wireless communication between the nodes. In this paper, trust-based intrusion detection system is proposed to calculate the trust by using MAC layer protocol. The trust value of each node in WSN is evaluated by deviation of key factor at the MAC layer. The ML-IDS is impressive system to detect the malicious nodes in wireless sensor network. The malicious nodes attack the MAC layer by Back-off manipulation attack. Mainly Back-off manipulation attack is used to reduce the back-off time to get the channel priority. We have implemented the back-off manipulation attack at MAC layer for performance evaluation. Results show that ML-IDS perform higher quality as compared to Wang et al. (Sensors 17(6):1227, 2017, [1]) based on detection accuracy and false alarm rate.

Wireless Sensor Network (WSN) suffers from different malware attacks. Several traditional approaches are proposed for detecting fault nodes in WSN. It is necessary to redistribute the nodes and detect the fault nodes while modifying the WSN parameters. Faults can occur in the nodes interrupting the continuous communication process of the nodes in the WSN. The main reason for a fault is also the induction of the energy drain in a node to the maximum possible level, failure of links in communicating nodes due to bandwidth constraints, and attacks induced by the malicious nodes. To solve this problems, Extended Finite State Machine based Fault Tolerance (EFSM_FT) in the WSN is used to detect the fault sensor nodes in the WSN. In this approach, called the finite state machine (FSM), state prompted is modified while a set of situations are true. Every node can be absolutely to be faulty or not establishing on the sensor node states. Using sensor energy, drop rate, forward sensor rate, sensor obtained rate, bandwidth, and transmission delay, this method finds the node with the fault. As a result, this approach accurately detects the faulty nodes in the WSN. The simulation outcomes illustrate the proposed method has a better fault detection ratio and minimizes the false negative ratio in the WSN.

For the past decade, wireless sensor networks have focused primarily on data collection. As a result the network topology for these systems was usually heavily centralized. However, for these networks to form a full system, the introduction of proper actuation units and decision-making intelligence is inevitable. Such a new wireless sensor and actuator network system enables new architectural research issues that have not been previously studied. In this work, we introduce the DWSAN system architecture, which effectively combines both sensor and actuation hardware devices to a single network and manages this network so that the actuation decisions are made in a distributed manner and the topology of the network maintains a multitier architecture. Our intensive set of evaluations reveal that, compared to the centralized approach that has been used in most wireless sensor network systems until now, when actuation units are introduced to the system, the DWSAN architecture reduces the transmission load of the network and the actuation decision-making latency by close to twofold and threefold, respectively. Furthermore, we show that this benefit naturally leads to better scalability of the system, making it suitable for various sensing applications in different environments.

Recently, the technology of wireless sensor networks (WSNs) experiences a growing use in home automation or advanced industry infrastructure applications. Despite a strong interest of industries in this technology, key issues like miniaturization and security of WSN nodes has not been solved yet. State-of-the-art WSN nodes do not provide credible security nor satisfying configurability and miniaturized implementations. This publication deals with these limitations and presents a WSN node that provides security, configurability, and a miniaturized design. To show the sensor node feasibility, the WSN node is implemented within a smart home demonstrator. Additionally, a miniaturized pre-study WSN node design is presented using the novel embedded wafer level ball grid array (eWLB) packaging technology. Furthermore, an eWLB based WSN node design is proposed that further miniaturize the presented WSN node.

Energy harvesting systems (EHSs) are the key to perpetual operation of electronic devices in application areas with bad infrastructure or mobility. Wireless sensor networks (WSNs) are often used in such areas. Normal WSN nodes are powered by batteries. Therefore, the lifetime is limited and the batteries have to be replaced manually after a certain period of time. This problem can be solved by EHSs. They exploit energy sources of the environment and store the harvested energy in energy buffers. The EHS supplies the electronic device and ensures a continuous operation. WSNs can benefit from these developments, because the lifetime can be enhanced dramatically. However, the EHS have to be adapted to the requirements of the application area and of the supplied device. This enhances the overall efficiency of EHS. To be able to do that, the fundamental mode of operation of an EHS has to be well-understood. We introduce a novel tier model for EHSs. It structures the EHS into tiers with special functions. This enhances the design process of an EHS, because tiers can be adapted to each other and the overall efficiency of can be increased. The tier model is applied to RiverMote, a WSN node for in-river water level monitoring. Each node is supplied by solar cells and the energy is stored in double layer capacitors (DLCs). The hardware of the EHS of RiverMote is divided into the tiers of the model. These tiers are adapted to each other carefully. Although no maximum power point tracker has been implemented, it has been shown that the available power of the solar cell is greater than 80 % of the maximum power point if the energy level of the DLCs is between 42 % and 100 %. This result was only possible by a careful design and an adaption of the tiers.

Over the past decades, hardware and software technologies for wireless sensor networks (WSNs) have significantly progressed, and WSNs are widely used in various areas including Internet of Things (IoT). In general, existing WSNs are mainly used for applications that require delay-tolerance and low-computation due to the poor resources of traditional sensor nodes in WSNs. However, compared to the traditional sensor nodes, today’s devices for WSNs have more powerful resource. Thus, sensor nodes these days not only conduct sensing and transmitting data to servers but also are able to process many operations, so more diverse applications can be applied to WSNs. Especially, many applications using audio data have been proposed because audio is one of the most widely used data types, and many mobile devices already have a built-in microphone. However, many of the applications have a requirement that heavy-operations should be done by a tight deadline, so it is difficult for a single node in WSNs to run relatively heavy applications by itself. In this paper, to overcome this limitation of WSNs, we propose a new emerging system, HeaLow, a cooperative computing system for heavy-computation and low-latency processing in WSNs. We designed HeaLow and carried out the practical implementation on real devices. We confirmed the effectiveness of HeaLow through various experiments using the real devices and simulations. Using HeaLow, nodes in WSNs are able to perform heavy-computation processes while satisfying a completion time requirement.

Self-powered wireless sensor networks based on the radioisotope thermoelectric generator for aquatic temperature monitoring