Quality of service aware ant colony optimization routing algorithm

The demand for Internet connectivity has grown exponentially in the past few years. Moreover, the advent of new services such as Voice over IP (VoIP), Video on Demand (VOD) and Videoconferencing applications have caused a sever increase in traffic, which makes it extremely hard to ensure an acceptable level of quality. This is mainly attributed to current routing strategies, such as Link State (LS) and Distance Vector (DV), which are not optimal in terms of Quality of Service (QoS). This paper presents a QoS-Aware routing strategy based on the Ant Colony Optimization (ACO) concept, where a set of artificial ants are used to determine the optimal path. The proposed method was compared to other state of the art ACO procedures and traditional routing schemes like LS and DV. Simulation results clearly demonstrate that the proposed scheme outperforms all the methods considered in this paper where throughput gains of 8% and a reduction in delay of 38% for time critical applications were achieved.peer-reviewe

A QoS-Aware Routing Protocol for Real-time Applications in Wireless Sensor Networks

The paper presents a quality of service aware routing protocol which provides low latency for high priority packets. Packets are differentiated based on their priority by applying queuing theory. Low priority packets are transferred through less energy paths. The sensor nodes interact with the pivot nodes which in turn communicate with the sink node. This protocol can be applied in monitoring context aware physical environments for critical applications.Comment: 10 pages. arXiv admin note: text overlap with arXiv:1001.5339 by other author

Quality of Service Aware Orchestration for Cloud-Edge Continuum Applications

The fast growth in the amount of connected devices with computing capabilities in the past years has enabled the emergence of a new computing layer at the Edge. Despite being resource-constrained if compared with cloud servers, they offer lower latencies than those achievable by Cloud computing. The combination of both Cloud and Edge computing paradigms can provide a suitable infrastructure for complex applications’ quality of service requirements that cannot easily be achieved with either of these paradigms alone. These requirements can be very different for each application, from achieving time sensitivity or assuring data privacy to storing and processing large amounts of data. Therefore, orchestrating these applications in the Cloud–Edge computing raises new challenges that need to be solved in order to fully take advantage of this layered infrastructure. This paper proposes an architecture that enables the dynamic orchestration of applications in the Cloud–Edge continuum. It focuses on the application’s quality of service by providing the scheduler with input that is commonly used by modern scheduling algorithms. The architecture uses a distributed scheduling approach that can be customized in a per-application basis, which ensures that it can scale properly even in setups with high number of nodes and complex scheduling algorithms. This architecture has been implemented on top of Kubernetes and evaluated in order to asses its viability to enable more complex scheduling algorithms that take into account the quality of service of applications.This work has been financially supported by the European Commission through the ELASTIC project (H2020 grant agreement 825473), by the Spanish Ministry of Science, Innovation and Universities (project RTI2018-096116-B-I00 (MCIU/AEI/FEDER, UE)), and by the Basque Government through the Qualyfamm project (Elkartek KK-2020/00042). It has also been financed by the Basque Government under Grant IT1324-19

Quality of service aware data dissemination in vehicular Ad Hoc networks

Des systèmes de transport intelligents (STI) seront éventuellement fournis dans un proche avenir pour la sécurité et le confort des personnes lors de leurs déplacements sur les routes. Les réseaux ad-hoc véhiculaires (VANETs) représentent l'élément clé des STI. Les VANETs sont formés par des véhicules qui communiquent entre eux et avec l'infrastructure. En effet, les véhicules pourront échanger des messages qui comprennent, par exemple, des informations sur la circulation routière, les situations d'urgence et les divertissements. En particulier, les messages d'urgence sont diffusés par des véhicules en cas d'urgence (p.ex. un accident de voiture); afin de permettre aux conducteurs de réagir à temps (p.ex., ralentir), les messages d'urgence doivent être diffusés de manière fiable dans un délai très court. Dans les VANETs, il existe plusieurs facteurs, tels que le canal à pertes, les terminaux cachés, les interférences et la bande passante limitée, qui compliquent énormément la satisfaction des exigences de fiabilité et de délai des messages d'urgence. Dans cette thèse, en guise de première contribution, nous proposons un schéma de diffusion efficace à plusieurs sauts, appelé Dynamic Partitioning Scheme (DPS), pour diffuser les messages d'urgence. DPS calcule les tailles de partitions dynamiques et le calendrier de transmission pour chaque partition; à l'intérieur de la zone arrière de l'expéditeur, les partitions sont calculées de sorte qu'en moyenne chaque partition contient au moins un seul véhicule; l'objectif est de s'assurer que seul un véhicule dans la partition la plus éloignée (de l'expéditeur) est utilisé pour diffuser le message, jusqu'au saut suivant; ceci donne lieu à un délai d'un saut plus court. DPS assure une diffusion rapide des messages d'urgence. En outre, un nouveau mécanisme d'établissement de liaison, qui utilise des tonalités occupées, est proposé pour résoudre le problème du problème de terminal caché. Dans les VANETs, la Multidiffusion, c'est-à-dire la transmission d'un message d'une source à un nombre limité de véhicules connus en tant que destinations, est très importante. Par rapport à la diffusion unique, avec Multidiffusion, la source peut simultanément prendre en charge plusieurs destinations, via une arborescence de multidiffusion, ce qui permet d'économiser de la bande passante et de réduire la congestion du réseau. Cependant, puisque les VANETs ont une topologie dynamique, le maintien de la connectivité de l'arbre de multidiffusion est un problème majeur. Comme deuxième contribution, nous proposons deux approches pour modéliser l'utilisation totale de bande passante d'une arborescence de multidiffusion: (i) la première approche considère le nombre de segments de route impliqués dans l'arbre de multidiffusion et (ii) la seconde approche considère le nombre d'intersections relais dans l'arbre de multidiffusion. Une heuristique est proposée pour chaque approche. Pour assurer la qualité de service de l'arbre de multidiffusion, des procédures efficaces sont proposées pour le suivi des destinations et la surveillance de la qualité de service des segments de route. Comme troisième contribution, nous étudions le problème de la congestion causée par le routage du trafic de données dans les VANETs. Nous proposons (1) une approche de routage basée sur l’infonuagique qui, contrairement aux approches existantes, prend en compte les chemins de routage existants qui relaient déjà les données dans les VANETs. Les nouvelles demandes de routage sont traitées de sorte qu'aucun segment de route ne soit surchargé par plusieurs chemins de routage croisés. Au lieu d'acheminer les données en utilisant des chemins de routage sur un nombre limité de segments de route, notre approche équilibre la charge des données en utilisant des chemins de routage sur l'ensemble des tronçons routiers urbains, dans le but d'empêcher, dans la mesure du possible, les congestions locales dans les VANETs; et (2) une approche basée sur le réseau défini par logiciel (SDN) pour surveiller la connectivité VANET en temps réel et les délais de transmission sur chaque segment de route. Les données de surveillance sont utilisées en entrée de l'approche de routage.Intelligent Transportation Systems (ITS) will be eventually provided in the near future for both safety and comfort of people during their travel on the roads. Vehicular ad-hoc Networks (VANETs), represent the key component of ITS. VANETs consist of vehicles that communicate with each other and with the infrastructure. Indeed, vehicles will be able to exchange messages that include, for example, information about road traffic, emergency situations, and entertainment. Particularly, emergency messages are broadcasted by vehicles in case of an emergency (e.g., car accident); in order to allow drivers to react in time (e.g., slow down), emergency messages must be reliably disseminated with very short delay. In VANETs, there are several factors, such as lossy channel, hidden terminals, interferences and scarce bandwidth, which make satisfying reliability and delay requirements of emergency messages very challenging. In this thesis, as the first contribution, we propose a reliable time-efficient and multi-hop broadcasting scheme, called Dynamic Partitioning Scheme (DPS), to disseminate emergency messages. DPS computes dynamic partition sizes and the transmission schedule for each partition; inside the back area of the sender, the partitions are computed such that in average each partition contains at least a single vehicle; the objective is to ensure that only a vehicle in the farthest partition (from the sender) is used to disseminate the message, to next hop, resulting in shorter one hop delay. DPS ensures fast dissemination of emergency messages. Moreover, a new handshaking mechanism, that uses busy tones, is proposed to solve the problem of hidden terminal problem. In VANETs, Multicasting, i.e. delivering a message from a source to a limited known number of vehicles as destinations, is very important. Compared to Unicasting, with Multicasting, the source can simultaneously support multiple destinations, via a multicast tree, saving bandwidth and reducing overall communication congestion. However, since VANETs have a dynamic topology, maintaining the connectivity of the multicast tree is a major issue. As the second contribution, we propose two approaches to model total bandwidth usage of a multicast tree: (i) the first approach considers the number of road segments involved in the multicast tree and (ii) the second approach considers the number of relaying intersections involved in the multicast tree. A heuristic is proposed for each approach. To ensure QoS of the multicasting tree, efficient procedures are proposed for tracking destinations and monitoring QoS of road segments. As the third contribution, we study the problem of network congestion in routing data traffic in VANETs. We propose (1) a Cloud-based routing approach that, in opposition to existing approaches, takes into account existing routing paths which are already relaying data in VANETs. New routing requests are processed such that no road segment gets overloaded by multiple crossing routing paths. Instead of routing over a limited set of road segments, our approach balances the load of communication paths over the whole urban road segments, with the objective to prevent, whenever possible, local congestions in VANETs; and (2) a Software Defined Networking (SDN) based approach to monitor real-time VANETs connectivity and transmission delays on each road segment. The monitoring data is used as input to the routing approach

A context-aware decision engine for content adaptation

Building a good content adaptation service for mobile devices poses many challenges. To meet these challenges, this quality-of-service-aware decision engine automatically negotiates for the appropriate adaptation decision for synthesizing an optimal content version.published_or_final_versio

Quality-of-Service-Aware Data Stream Processing

Data stream processing in the industrial as well as in the academic field has gained more and more importance during the last years. Consider the monitoring of industrial processes as an example. There, sensors are mounted to gather lots of data within a short time range. Storing and post-processing these data may occasionally be useless or even impossible. On the one hand, only a small part of the monitored data is relevant. To efficiently use the storage capacity, only a preselection of the data should be considered. On the other hand, it may occur that the volume of incoming data is generally too high to be stored in time or–in other words–the technical efforts for storing the data in time would be out of scale. Processing data streams in the context of this thesis means to apply database operations to the stream in an on-the-fly manner (without explicitly storing the data). The challenges for this task lie in the limited amount of resources while data streams are potentially infinite. Furthermore, data stream processing must be fast and the results have to be disseminated as soon as possible. This thesis focuses on the latter issue. The goal is to provide a so-called Quality-of-Service (QoS) for the data stream processing task. Therefore, adequate QoS metrics like maximum output delay or minimum result data rate are defined. Thereafter, a cost model for obtaining the required processing resources from the specified QoS is presented. On that basis, the stream processing operations are scheduled. Depending on the required QoS and on the available resources, the weight can be shifted among the individual resources and QoS metrics, respectively. Calculating and scheduling resources requires a lot of expert knowledge regarding the characteristics of the stream operations and regarding the incoming data streams. Often, this knowledge is based on experience and thus, a revision of the resource calculation and reservation becomes necessary from time to time. This leads to occasional interruptions of the continuous data stream processing, of the delivery of the result, and thus, of the negotiated Quality-of-Service. The proposed robustness concept supports the user and facilitates a decrease in the number of interruptions by providing more resources

Quality of Service Aware Dynamic Bandwidth Allocation for Rate Control in WSN

Different types of data can be generated by Wireless Sensor Networks (WSNs) in both Real-Time (RT) and Non-RT (NRT) scenarios. The combination of these factors, along with the limited bandwidth available, necessitates careful management of these categories in order to reduce congestion. Due to this, a Proficient Rate Control  and Fair Bandwidth Allocation (PRC-FBA) method has been created that prioritizes certain types of traffic and creates a virtual queue for them.In PRC-FBA, the Signal-to-Noise and Interference Ratio (SINR) model is applied to the problem of bandwidth allocation in WSN in an effort to find a compromise between equity and performance. Then, a brand-new bandwidth utility factor is defined with regard to equity and effectivenes. The FBA method in PRC-FBA is devoped for only improving   throughput, but not considering  delay. However, delay is the main factors for trasnmiitng NRT packets.  This paper offers a PRC with Quality of Service (QoS) aware Dynamic Bandwidth Allocation (PRC-QDBA) approach for allocating bandwidth while prioritizing packets based on their traffic classes. This model employs a QoS associated dynamic bandwidth allocation strategy which efficiently distributes the unused time slots among the required nodes. The distribution technique is performed based on hierarchical manner utilizing a parent-child association of tree topology. The parent node receives traffic indication maps (TIMs) from the children nodes and adopts them to allocate time slots based on their demamds. If the parent node is unable to allocate the required slots, it creates a TIM that indicating the demands and transfer it to its immediate parent node. This increases the entire performance rate of RT traffic. Furthermore, this model assures the packet forwarding for previously accepted flows by allowing node transmission based on ancestral connection capabilities. Finally, simulation results demonstartes that the suggested model significantly increases the throughput and delay for bandwidth allocation while also enabling QoS support for RT traffic in WSNs.&nbsp

Quality of Service Aware Data Stream Processing for Highly Dynamic and Scalable Applications

Huge amounts of georeferenced data streams are arriving daily to data stream management systems that are deployed for serving highly scalable and dynamic applications. There are innumerable ways at which those loads can be exploited to gain deep insights in various domains. Decision makers require an interactive visualization of such data in the form of maps and dashboards for decision making and strategic planning. Data streams normally exhibit fluctuation and oscillation in arrival rates and skewness. Those are the two predominant factors that greatly impact the overall quality of service. This requires data stream management systems to be attuned to those factors in addition to the spatial shape of the data that may exaggerate the negative impact of those factors. Current systems do not natively support services with quality guarantees for dynamic scenarios, leaving the handling of those logistics to the user which is challenging and cumbersome. Three workloads are predominant for any data stream, batch processing, scalable storage and stream processing. In this thesis, we have designed a quality of service aware system, SpatialDSMS, that constitutes several subsystems that are covering those loads and any mixed load that results from intermixing them. Most importantly, we natively have incorporated quality of service optimizations for processing avalanches of geo-referenced data streams in highly dynamic application scenarios. This has been achieved transparently on top of the codebases of emerging de facto standard best-in-class representatives, thus relieving the overburdened shoulders of the users in the presentation layer from having to reason about those services. Instead, users express their queries with quality goals and our system optimizers compiles that down into query plans with an embedded quality guarantee and leaves logistic handling to the underlying layers. We have developed standard compliant prototypes for all the subsystems that constitutes SpatialDSMS