902 research outputs found

    Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks

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    لضمان الإستجابة للخطأ والإدارة الموزعة، يتم استخدام البروتوكولات الموزعة كأحد المفاهيم المعمارية الرئيسية التي تتضمنها شبكة الإنترنت. ومع ذلك، يمكن التغلب على عدم الكفاءة وعدم الاستقرار والقصور بمساعدة بنية الشبكات الجديدة التي تسمى الشبكات المعرفة بالبرمجيات SDN. الخاصية الرئيسية لهذه المعمارية هي فصل مستوى التحكم عن مستوى البيانات. إن تقليل التصادم سيؤدي إلى تحسين سرعة الإستجابة وزيادة البيانات المرسلة بصورة صحيحة، لهذا السبب يجب أن يكون هناك توزيع متجانس للحمل المروري عبر مسارات الشبكة المختلفة. تقدم هذه الورقة البحثية أداة توجيه ذكية SFSA لتوجيه تدفق البيانات بناءاً على ظروف الشبكة الحالية. لتحسين الإنتاجية وتقليل زمن الوصول، فإن الخوارزمية المقترحة SFSA تقوم بتوزيع حركة مرور البيانات داخل الشبكة على مسارات مناسبة ، بالإضافة إلى الإشراف على الإرتباطات التشعبية وحمل مسارات نقل البيانات. تم استخدام سيناريو خوارزمية توجيه شجرة الامتداد الدنياMST وأخرى مع خوارزمية التوجيه المعروفة بفتح أقصر مسار أولاً OSPF لتقييم جودة الخوارمية المقترحة SFSA . على سبيل المقارنة ، بالنسبة لخوارزميات التوجيه المذكروة آنفاً ، فقد حققت استراتيجيةSFSA المقترحة انخفاضاً بنسبة 2٪ في معدل ضياع حزم البيانات PDR ، وبنسبة تتراوح بين 15-45٪ في سرعة إستلام البيانات من المصدر إلى الالوجهة النهائية لحزمة البيانات وكذلك انخفاض بنسبة 23 ٪ في زمن رحلة ذهاب وعودة RTT . تم استخدام محاكي Mininet ووحدة التحكم POX لإجراء المحاكاة. ميزة أخرى من SFSA على MST و OSPF هي أن وقت التنفيذ والاسترداد لا يحمل تقلبات. يتقوم أداة التوجيه الذكية المقترحة في هذه الورقة البحثية من فتح أفقاً جديداً لنشر أدوات ذكية جديدة في شبكة SDN تعزز قابلية برمجة الشبكات وإدارتها .To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management

    A COMMUNICATION FRAMEWORK FOR MULTIHOP WIRELESS ACCESS AND SENSOR NETWORKS: ANYCAST ROUTING & SIMULATION TOOLS

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    The reliance on wireless networks has grown tremendously within a number of varied application domains, prompting an evolution towards the use of heterogeneous multihop network architectures. We propose and analyze two communication frameworks for such networks. A first framework is designed for communications within multihop wireless access networks. The framework supports dynamic algorithms for locating access points using anycast routing with multiple metrics and balancing network load. The evaluation shows significant performance improvement over traditional solutions. A second framework is designed for communication within sensor networks and includes lightweight versions of our algorithms to fit the limitations of sensor networks. Analysis shows that this stripped down version can work almost equally well if tailored to the needs of a sensor network. We have also developed an extensive simulation environment using NS-2 to test realistic situations for the evaluations of our work. Our tools support analysis of realistic scenarios including the spreading of a forest fire within an area, and can easily be ported to other simulation software. Lastly, we us our algorithms and simulation environment to investigate sink movements optimization within sensor networks. Based on these results, we propose strategies, to be addressed in follow-on work, for building topology maps and finding optimal data collection points. Altogether, the communication framework and realistic simulation tools provide a complete communication and evaluation solution for access and sensor networks

    SURF: A Distributed Channel Selection Strategy for Data Dissemination in Multi-Hop Cognitive Radio Networks

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    In this paper, we propose an intelligent and distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio network. Our strategy, SURF, classifies the available channels and uses them efficiently to increase data dissemination reliability in multi-hop cognitive radio networks. The classification is done on the basis of primary radio unoccupancy and of the number of cognitive radio neighbors using the channels. Through extensive NS-2 simulations, we study the performance of SURF compared to three related approaches. Simulation results confirm that our approach is effective in selecting the best channels for efficient communication (in terms of less primary radio interference) and for highest dissemination reachability in multi-hop cognitive radio networks

    Enabling multicast slices in edge networks

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    Telecommunication networks are undergoing a disruptive transition towards distributed mobile edge networks with virtualized network functions (VNFs) (e.g., firewalls, Intrusion Detection Systems (IDSs), and transcoders) within the proximity of users. This transition will enable network services, especially IoT applications, to be provisioned as network slices with sequences of VNFs, in order to guarantee the performance and security of their continuous data and control flows. In this paper we study the problems of delay-aware network slicing for multicasting traffic of IoT applications in edge networks. We first propose exact solutions by formulating the problems into Integer Linear Programs (ILPs). We further devise an approximation algorithm with an approximation ratio for the problem of delay-aware network slicing for a single multicast slice, with the objective to minimize the implementation cost of the network slice subject to its delay requirement constraint. Given multiple multicast slicing requests, we also propose an efficient heuristic that admits as many user requests as possible, through exploring the impact of a non-trivial interplay of the total computing resource demand and delay requirements. We then investigate the problem of delay-oriented network slicing with given levels of delay guarantees, considering that different types of IoT applications have different levels of delay requirements, for which we propose an efficient heuristic based on Reinforcement Learning (RL). We finally evaluate the performance of the proposed algorithms through both simulations and implementations in a real test-bed. Experimental results demonstrate that the proposed algorithms is promising

    Datacenter Traffic Control: Understanding Techniques and Trade-offs

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    Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
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