Multi-objective hierarchical algorithms for restoring Wireless Sensor Network connectivity in known environments

A Wireless Sensor Network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. We propose a family of algorithms based on hierarchical objectives including complete algorithms and heuristics which integrate network design with path planning, recognising the impact of obstacles on mobility and communication. We conduct an empirical evaluation of the algorithms on random connectivity and mobility graphs, showing their relative performance in terms of node and path costs, and assessing their execution speeds. Finally, we examine how the relative importance of the two objectives influences the choice of algorithm. In summary, the algorithms which prioritise the node cost tend to find graphs with fewer nodes, while the algorithm which prioritise the cost of moving find slightly larger solutions but with cheaper mobility costs. The heuristic algorithms are close to the optimal algorithms in node cost, and higher in mobility costs. For fast moving agents, the node algorithms are preferred for total restoration time, and for slow agents, the path algorithms are preferred

Self-Organizing Mobility Control in Wireless Sensor and Actor Networks Based on Virtual Electrostatic Interactions

This paper introduces a new mobility control method for surveillance applications of wireless sensor and actor networks. The proposed method is based on virtual electrostatic forces which act on actors to coordinate their movements. The definition of virtual forces is inspired by Coulomb’s law from physics. Each actor calculates the virtual forces independently based on known locations of its neighbours and predetermined borders of the monitored area. The virtual forces generate movements of actors. This approach enables effective deployment of actors at the initial stage as well as adaptation of actors’ placement to variable conditions during execution of the surveillance task without the need of any central controller. Effectiveness of the introduced method was experimentally evaluated in a simulation environment. The experimental results demonstrate that the proposed method enables more effective organization of the actors’ mobility than state-of-the-art approaches

Twin Delayed DDPG based Dynamic Power Allocation for Mobility in IoRT

The internet of robotic things (IoRT) is a modern as well as fast-evolving technology employed in abundant socio-economical aspects which connect user equipment (UE) for communication and data transfer among each other. For ensuring the quality of service (QoS) in IoRT applications, radio resources, for example, transmitting power allocation (PA), interference management, throughput maximization etc., should be efficiently employed and allocated among UE. Traditionally, resource allocation has been formulated using optimization problems, which are then solved using mathematical computer techniques. However, those optimization problems are generally nonconvex as well as nondeterministic polynomial-time hardness (NP-hard). In this paper, one of the most crucial challenges in radio resource management is the emitting power of an antenna called PA, considering that the interfering multiple access channel (IMAC) has been considered. In addition, UE has a natural movement behavior that directly impacts the channel condition between remote radio head (RRH) and UE. Additionally, we have considered two well-known UE mobility models i) random walk and ii) modified Gauss-Markov (GM). As a result, the simulation environment is more realistic and complex. A data-driven as well as model-free continuous action based deep reinforcement learning algorithm called twin delayed deep deterministic policy gradient (TD3) has been proposed that is the combination of policy gradient, actor-critics, as well as double deep Q-learning (DDQL). It optimizes the PA for i) stationary UE, ii) the UE movements according to random walk model, and ii) the UE movement based on the modified GM model. Simulation results show that the proposed TD3 method outperforms model-based techniques like weighted MMSE (WMMSE) and fractional programming (FP) as well as model-free algorithms, for example, deep Q network (DQN) and DDPG in terms of average sum-rate performance

Routing protocol optimization in challenged multihop wireless networks

Durant ces dernières années, de nombreux travaux de recherches ont été menés dans le domaine des réseaux multi-sauts sans fil à contraintes (MWNs: Multihop Wireless Networks). Grâce à l'évolution de la technologie des systèmes mico-electro-méchaniques (MEMS) et, depuis peu, les nanotechnologies, les MWNs sont une solution de choix pour une variété de problèmes. Le principal avantage de ces réseaux est leur faible coût de production qui permet de développer des applications ayant un unique cycle de vie. Cependant, si le coût de fabrication des nœuds constituant ce type de réseaux est assez faible, ces nœuds sont aussi limités en capacité en termes de: rayon de transmission radio, bande passante, puissance de calcul, mémoire, énergie, etc. Ainsi, les applications qui visent l'utilisation des MWNs doivent être conçues avec une grande précaution, et plus spécialement la conception de la fonction de routage, vu que les communications radio constituent la tâche la plus consommatrice d'énergie.Le but de cette thèse est d'analyser les différents défis et contraintes qui régissent la conception d'applications utilisant les MWNs. Ces contraintes se répartissent tout le long de la pile protocolaire. On trouve au niveau application des contraintes comme: la qualité de service, la tolérance aux pannes, le modèle de livraison de données au niveau application, etc. Au niveau réseau, on peut citer les problèmes de la dynamicité de la topologie réseau, la présence de trous, la mobilité, etc. Nos contributions dans cette thèse sont centrées sur l'optimisation de la fonction de routage en considérant les besoins de l'application et les contraintes du réseau. Premièrement, nous avons proposé un protocole de routage multi-chemin "en ligne" pour les applications orientées QoS utilisant des réseaux de capteurs multimédia. Ce protocole repose sur la construction de multiples chemins durant la transmission des paquets vers leur destination, c'est-à-dire sans découverte et construction des routes préalables. En permettant des transmissions parallèles, ce protocole améliore la transmission de bout-en-bout en maximisant la bande passante du chemin agrégé et en minimisant les délais. Ainsi, il permet de répondre aux exigences des applications orientées QoS.Deuxièmement, nous avons traité le problème du routage dans les réseaux mobiles tolérants aux délais. Nous avons commencé par étudier la connectivité intermittente entre les différents et nous avons extrait un modèle pour les contacts dans le but pouvoir prédire les future contacts entre les nœuds. En se basant sur ce modèle, nous avons proposé un protocole de routage, qui met à profit la position géographique des nœuds, leurs trajectoires, et la prédiction des futurs contacts dans le but d'améliorer les décisions de routage. Le protocole proposé permet la réduction des délais de bout-en-bout tout en utilisant d'une manière efficace les ressources limitées des nœuds que ce soit en termes de mémoire (pour le stockage des messages dans les files d'attentes) ou la puissance de calcul (pour l'exécution de l'algorithme de prédiction).Finalement, nous avons proposé un mécanisme de contrôle de la topologie avec un algorithme de routage des paquets pour les applications orientés évènement et qui utilisent des réseaux de capteurs sans fil statiques. Le contrôle de la topologie est réalisé à travers l'utilisation d'un algorithme distribué pour l'ordonnancement du cycle de service (sleep/awake). Les paramètres de l'algorithme proposé peuvent être réglés et ajustés en fonction de la taille du voisinage actif désiré (le nombre moyen de voisin actifs pour chaque nœud). Le mécanisme proposé assure un compromis entre le délai pour la notification d'un événement et la consommation d'énergie globale dans le réseau.Great research efforts have been carried out in the field of challenged multihop wireless networks (MWNs). Thanks to the evolution of the Micro-Electro-Mechanical Systems (MEMS) technology and nanotechnologies, multihop wireless networks have been the solution of choice for a plethora of problems. The main advantage of these networks is their low manufacturing cost that permits one-time application lifecycle. However, if nodes are low-costly to produce, they are also less capable in terms of radio range, bandwidth, processing power, memory, energy, etc. Thus, applications need to be carefully designed and especially the routing task because radio communication is the most energy-consuming functionality and energy is the main issue for challenged multihop wireless networks.The aim of this thesis is to analyse the different challenges that govern the design of challenged multihop wireless networks such as applications challenges in terms of quality of service (QoS), fault-tolerance, data delivery model, etc., but also networking challenges in terms of dynamic network topology, topology voids, etc. Our contributions in this thesis focus on the optimization of routing under different application requirements and network constraints. First, we propose an online multipath routing protocol for QoS-based applications using wireless multimedia sensor networks. The proposed protocol relies on the construction of multiple paths while transmitting data packets to their destination, i.e. without prior topology discovery and path establishment. This protocol achieves parallel transmissions and enhances the end-to-end transmission by maximizing path bandwidth and minimizing the delays, and thus meets the requirements of QoS-based applications. Second, we tackle the problem of routing in mobile delay-tolerant networks by studying the intermittent connectivity of nodes and deriving a contact model in order to forecast future nodes' contacts. Based upon this contact model, we propose a routing protocol that makes use of nodes' locations, nodes' trajectories, and inter-node contact prediction in order to perform forwarding decisions. The proposed routing protocol achieves low end-to-end delays while using efficiently constrained nodes' resources in terms of memory (packet queue occupancy) and processing power (forecasting algorithm). Finally, we present a topology control mechanism along a packet forwarding algorithm for event-driven applications using stationary wireless sensor networks. Topology control is achieved by using a distributed duty-cycle scheduling algorithm. Algorithm parameters can be tuned according to the desired node's awake neighbourhood size. The proposed topology control mechanism ensures trade-off between event-reporting delay and energy consumption.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

A Novel Communication Approach For Wireless Mobile Smart Objects

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2007Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2007Telsiz ağlar gezgin kullanıcılara nerede olduklarına bağlı olmadan her yerde iletişim kurma ve bilgiye erişim imkanı sağlar. Hiçbir sabit altyapıya gerek duymadan bu imkanı sağlayan tasarsız ağların zaman içinde gelişmesiyle, askeri, ticari ve özel maksatlar için tercih edilir hale gelmiştir. Diğer yandan, bilimsel ve teknolojik gelişmeler ağ elemanlarını daha küçük ve ucuz hale getirdikçe birçok uygulamanın vazgeçilmez parçaları olmuşlardır. Bu ağ elemanları, taşıyıcılara (örneğin gemiler, uçaklar, büyük araçlar, arabalar, insanlar, hayvanlar, vb.) monteli nesneler veya kendi taşıyıcısı olan (aktörler, duyargalar) nesneler olabilir. Fakat bu ağ elemanları ve uygulamalarında bir takım zorluklar yaşanmaktadır. Bu tezde, gezgin tasarsız ve duyarga ağlardaki yaşanan zorlukları ve beklentileri dikkate alarak, gezgin tasarsız ve duyarga ağlar için yeni bir özgün, durumsuz veri akış yaklaşımı ve yönlendirme algoritması önerilmektedir. Durumsuz Ağırlıklı Yönlendirme (DAY, “Stateless Weighted Routing – SWR”) algoritması olarak adlandırdığımız bu algoritma, diğer yöntemlere göre daha az yönlendirme yükü, daha az enerji tüketimi, daha az yol oluşturma gecikmesi sağlamaktadır. Veri, varışa doğru, çoklu yollar üzerinden taşınmaktadır. Çoklu yol oluşturma, güvenirliği sağlamakta, boşluk problemini büyük oranda çözmekte ve en kısa yolu da içeren daha gürbüz yollar oluşmasını sağlamaktadır. DAY aynı zamanda büyük ölçekli ağlarda da uygulanabilir. Bu amaçla, birden fazla veri toplanma düğümü (sink) içeren sürümü olan Çoklu Veri Toplanma Düğümlü- Durumsuz Ağırlıklı Yönlendirme (ÇVTD-DAY - “Multiple Sink-Stateless Weighted Routing - MS-SWR”) yöntemi de büyük ölçekli tasarsız ve duyarga ağları için önerilmiştir. ÇVTD-DAY yöntemi, DAY yönteminde herhangi bir yöntemsel ve algoritmik değişiklik yapmadan birden fazla veri toplanma düğümünün olduğu ağlarda uygulanabilir. Hem DAY, hem ÇVTD-DAY’nin başarımı benzetimler ile ölçüldü. Elde edilen sonuçlar, DAY ‘nin gezgin tasarsız ve duyarga ağlar için istenenleri karşıladığını, karşılaştırılan diğer yöntemlere göre üstün olduğunu ve olası en iyi çözüme yakınlığını, öte yandan ÇVTD-DAY‘nin de büyük ölçekli ağlarda uygulanabilir olduğunu göstermektedir.Wireless networks provide mobile user with ubiquitous communication capability and information access regardless of location. Mobile ad hoc networks, that manage it without a need to infrastructure networks, as evolved in time, become more preferable for military, commercial and special purposes. On the other hand, technological advances made network components smaller and cheaper. These network components involves a wide variety of objects such as objects mounted on crafts/platforms (e.g. ships, aircrafts, trucks, cars, humans, animals), and objects that have their own platforms (e.g. actuators, sensor nodes). However, these network components and their involved applications exhibit some challenges to implement. By considering the challenges and expectations of mobile ad hoc networks and sensor network, we propose a novel stateless data flow approach and routing algorithm namely Stateless Weighted Routing (SWR) for mobile ad hoc and sensor networks. The SWR has low routing overhead providing very low energy consumption, and has low route construction delay than other proposed schemes. Multiple paths to the destination are established for data transmission. Constructing multiple paths provides reliability, eliminates the void problem substantially, and provides more robust routes including the shortest path. The SWR is applicable to large scale networks. We propose the multiple-sink version of the SWR that is namely MS-SWR, to be used in large scale ad hoc and sensor networks with multiple sinks. The MS-SWR can be used with multiple sinks without any functional and algorithmic modification in the SWR protocol. The performance of the SWR and the MS-SWR are evaluated by simulations. The performance of the system shows that the SWR satisfies the requirements of mobile ad hoc networks and outperforms the existing algorithms. The SWR is also tested against a hypothetic routing scheme that finds the shortest available path with no cost in order to compare the performance of the SWR against such an ideal case. Tests also indicate that MS-SWR is scalable for large scale networks.DoktoraPh

Deployment Policies to Reliably Maintain and Maximize Expected Coverage in a Wireless Sensor Network

The long-term operation of a wireless sensor network (WSN) requires the deployment of new sensors over time to restore any loss in network coverage and communication ability resulting from sensor failures. Over the course of several deployment actions it is important to consider the cost of maintaining the WSN in addition to any desired performance measures such as coverage, connectivity, or reliability. The resulting problem formulation is approached first through a time-based deployment model in which the network is restored to a fixed size at periodic time intervals. The network destruction spectrum (D-spectrum) has been introduced to estimate reliability and is more commonly applied to a static network, rather than a dynamic network where new sensors are deployed over time. We discuss how the D-spectrum can be incorporated to estimate reliability of a time-based deployment policy and the features that allow a wide range of deployment policies to be evaluated in an efficient manner. We next focus on a myopic condition-based deployment model where the network is observed at periodic time intervals and a fixed budget is available to deploy new sensors with each observation. With a limited budget available the model must address the complexity present in a dynamic network size in addition to a dynamic network topology, and the dependence of network reliability on the deployment action. We discuss how the D-spectrum can be applied to the myopic condition-based deployment problem, illustrating the value of the D-spectrum in a variety of maintenance settings beyond the traditional static network reliability problem. From the insight of the time-based and myopic condition-based deployment models, we present a Markov decision process (MDP) model for the condition-based deployment problem that captures the benefit of an action beyond the current time period. Methodology related to approximate dynamic programming (ADP) and approximate value iteration algorithms is presented to search for high quality deployment policies. In addition to the time-based and myopic condition-based deployment models, the MDP model is one of the few addressing the repeated deployment of new sensors as well as an emphasis on network reliability. For each model we discuss the relevant problem formulation, methodology to estimate network reliability, and demonstrate the performance in a range of test instances, comparing to alternative policies or models as appropriate. We conclude with a stochastic optimization model focused on a slightly different objective to maximize expected coverage with uncertainty in where a sensor lands in the network. We discuss a heuristic solution method that seeks to determine an optimal deployment of sensors, present results for a wide range of network sizes and explore the impact of sensor failures on both the model formulation and resulting deployment policy

Orta Doğu Teknik Üniversitesi- Bilgi Toplumu Teknolojileri- Mükemmeliyet merkez projesi

TÜBİTAK EEEAG Proje01.02.200

Lifetime and Energy Hole Evolution Analysis in Data-Gathering Wireless Sensor Networks

Abstract-Network lifetime is a crucial performance metric to evaluate data-gathering wireless sensor networks (WSNs) where battery-powered sensor nodes periodically sense the environment and forward collected samples to a sink node. In this paper, we propose an analytic model to estimate the entire network lifetime from network initialization until it is completely disabled, and determine the boundary of energy hole in a data-gathering WSN. Specifically, we theoretically estimate the traffic load, energy consumption, and lifetime of sensor nodes during the entire network lifetime. Furthermore, we investigate the temporal and spatial evolution of energy hole, and apply our analytical results to WSN routing in order to balance the energy consumption and improve the network lifetime. Extensive simulation results are provided to demonstrate the validity of the proposed analytic model in estimating the network lifetime and energy hole evolution process. Index Terms-wireless sensor network, network lifetime, energy hole, energy efficiency, routing

Algorithms for task assignment in wireless networks of microcontroller sensor nodes and autonomous robots

U bežičnoj mreži senzora i robota, senzorski moduli vrše nadzor fizičkih veličina od značaja, a roboti imaju ulogu izvršilaca zadataka koji im se dodeljuju primenom odgovarajućeg algoritma. Nakon detekcije događaja od strane statičkih senzorskih čvorova i prosleđivanja informacija o događajima robotima, potrebno je dodeliti zadatke robotima na efikasan način. Dodela zadataka vrši se u skladu sa prirodom različitih scenarija koji se mogu javiti u praksi. U okviru disertacije razmatran je slučaj kada se konkurentno javlja više događaja kojima je potrebno dodeliti izvršioce. U pogledu energetske efikasnosti, u ovakvim sistemima kao ključni problemi javljaju se minimizacija ukupne dužine kretanja robota i optimizacija komunikacije u mreži. Od komunikacinih protokola za otkrivanje izvršilaca, u ovoj disertaciji predstavljena su poboljšanja postojećeg iMesh protokola i uveden je novi vCell protokol zasnovan na lokalizovanom formiranju ćelija Voronoi dijagrama. Takođe, upoređene su performanse novog protokola sa postojećim (pravougaoni kvorum i iMesh) u gustim mrežama, retkim mrežama i mrežama sa rupama u topologiji. Uz to, uvedeni su algoritmi za ažuriranje lokacije kojima mreža reaguje na kretanje robota. Rezultati simulacija pokazuju da vCell postiže efikasnost blizu 100% u nalaženju najbližeg robota u gustim mrežama. U retkim mrežama, efikasnost mu je do 40% bolja u odnosu na ostala rešenja. Kao glavni rezultat u disertaciji prikazani su novi algoritmi za dodelu robota kao izvršilaca zadataka događajima, čime su prevaziđni nedostaci više do sada poznatih rešenja ovog problema. Za zadati skup događaja i skup robota, svakom događaju dodeljen je po jedan robot koji je zadužen za obilazak lokacije događaja. Tokom pojedinačnih rundi, robotima je dozvoljen obilazak jednog događaja kada se vrši uparivanje, ili više događaja, kada se vrši sekvencijalna dodela. U distribuiranom slučaju, statički senzorski uređaji detektuju događaje i prijavljuju ih obližnjim robotima. Algoritam PDM koji se odnosi na unapređeno uparivanje sa mogućnošću razmene partnera, eliminiše dugačke ivice koje se mogu javiti prilikom uparivanja. Algoritam SQD za sekvencijalnu dodelu događaja robotima iterativno pronalazi par robot-događaj sa najmanjim međusobnim rastojanjem, uvrštava izabrani događaj u listu za oblazak izabranog robota i ažurira poziciju robota. Takođe su predložene generalizacije koje omogućavaju da događaji budu posećeni od strane više robota i koje uzimaju u obzir vremenska ograničenja. Distribuirani algoritam MAD, koji je zasnovan na iMesh informacionoj strukturi i lokalnim aukcijama u robotskoj mreži, vrši dodelu robota događajima na lokalizovan i energetski efikasan način. Rezultati simulacija potvrđuju prednosti predloženih algoritama u odnosu na postojeća rešenja, kako u pogledu skraćivanja dužina putanja robota, tako i u produženju životnog vremena sistema.In a typical wireless sensor and robot network, sensor nodes monitor physical values of interest, while robots perform some automated tasks. The tasks are assigned to robots by means of an appropriate algorithm. Upon the occurrence of events which are detected by sensor nodes, the information about the events needs to be delivered to robots. Afterwards, it is necessary to assign tasks to robots in an efficient way. Task assignment is performed according to the nature of different scenarios which might occur in practice. This thesis is focused on the case when multiple events, all of which require to be visited by robots, happen simultaneously. Regarding energy efficiency, the key issues which arise in such systems are minimization of robot travel paths, and optimization of the network traffic. In this thesis, the following service discovery protocols are presented: improvements of the existing iMesh protocol, and the novel vCell protocol, which is based on localized formation of an information structure which resembles Voronoi diagram. Furthermore, the performaces of new vCell protocol is compared with the existing protocols (Quorum and iMesh) in dense networks, sparse networks, and networks with holes in topology. Also, location update algorithms are introduced, which deal with robot mobility. The simulations show that vCell achieves nearly 100% success rate in finding the nearest robot in dense networks. In sparse networks, it outperforms the other existing solutions by up to 40%. As a key contributtion, the novel dispatch lgorithms have been introduced. Given a set of events and a set of robots, the dispatch problem is to allocate one robot for each event to visit it. In a single round, each robot may be allowed to visit only one event (matching dispatch), or several events in a sequence (sequence dispatch). In a distributed setting, each event is discovered by a sensor and reported to a robot. In this thesis, novel algorithms are presented, whichh are aimed at overcoming the shortcomings of several existing solutions. Pairwise distance based matching algorithm (PDM) eliminates long edges by pairwise exchanges between matching pairs. Sequence dispatch algorithm (SQD) iteratively finds the closest event-robot pair, includes the event in dispatch schedule of the selected robot and updates its position accordingly. When event-robot distances are multiplied by robot resistance (inverse of the remaining energy), the corresponding energybalanced variants are obtained. Also, generalizations are introduced which handle multiple visits and timing constraints. Distributed algorithm MAD is based on information mesh infrastructure and local auctions within the robot network for obtaining the optimal dispatch schedule for each robot. The simulations conducted confirm the advantages of our algorithms over other existing solutions in terms of average robot-event distance and lifetime

Towards Aggregating Time-Discounted Information in Sensor Networks

Sensor networks are deployed to monitor a seemingly endless list of events in a multitude of application domains. Through data collection and aggregation enhanced with data mining and machine learning techniques, many static and dynamic patterns can be found by sensor networks. The aggregation problem is complicated by the fact that the perceived value of the data collected by the sensors is affected by many factors such as time, location and user valuation. In addition, the value of information deteriorates often dramatically over time. Through our research, we already achieved some results: A formal algebraic analysis of information discounting, especially affected by time. A general model and two specific models are developed for information discounting. The two specific models formalize exponetial time-discount and linear time-discount. An algebraic analysis of aggregation of values that decay with time exponentially. Three types of aggregators that offset discounting effects are formalized and analyzed. A natural synthesis of these three aggregators is discovered and modeled. We apply our theoretical models to emergency response with thresholding and confirm with extensive simulation. For long-term monitoring tasks, we laid out a theoretical foundation for discovering an emergency through generations of sensors, analysed the achievability of a long-term task and found an optimum way to distribute sensors in a monitored area to maximize the achievability. We proposed an implementation for our alert system with state-of-art wireless microcontrollers, sensors, real-time operating systems and embedded internet protocols. By allowing aggregation of time-discounted information to proceed in an arbitrary, not necessarily pairwise manner, our results are also applicable to other similar homeland security and military application domains where there is a strong need to model not only timely aggregation of data collected by individual sensors, but also the dynamics of this aggregation. Our research can be applied to many real-world scenarios. A typical scenario is monitoring wildfire in the forest: A batch of first-generation sensors are deployed by UAVs to monitor a forest for possible wildfire. They monitor various weather quantities and recognize the area with the highest possibility of producing a fire --- the so-called area of interest (AoI). Since the environment changes dynamically, so after a certain time, the sensors re-identify the AoI. The value of the knowledge they learned about the previous AoI decays with time quickly, our methods of aggregation of time-discounted information can be applied to get update knowledge. Close to depletion of their energy of the current generation of sensors, a new generation of sensors are deployed and inherit the knowledge from the current generation. Through this way, monitoring long-term tasks becomes feasible. At the end of this thesis, we propose some extensions and directions from our current research: Generalize and extend the special classes of Type 1 and Type 2 aggregation operators; Analyze aggregation operator of Type 3 and Type 4, find some special applicable candidates; Data aggregation across consecutive generations of sensors in order to learn about events with discounting that take a long time to manifest themselves; Network implications of various aggregation strategies; Algorithms for implementation of some special classes of aggregators. Implement wireless sensor network that can autonomously learn and recognize patterns of emergencies, predict incidents and trigger alarms through machine learning