اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدA Software-Defined Solution for Managing Fog Computing Resources in Sensor Networks
71
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The fast growth of Internet-connected embedded devices demands for new capabilities at the network edge. These new capabilities are local processing, fast communications, and resource virtualization. The current work aims to address the previous capabilities by designing and deploying a new proposal, which offers on-demand activation of offline IoT fog computing assets via a Software Defined Networking (SDN) based solution combined with containerization and sensor virtualization. We present and discuss performance and functional outcomes from emulated tests made on our proposal. Analysing the performance results, the system latency has two parts. The first part is about the delay induced by limitations on the networking resources. The second part of the system latency is due to the on-demand activation of the required processing resources, which are initially powered off towards a more sustainable system operation. In addition, analysing the functional results, when a real IoT protocol is used, we evidence our proposal viability to be deployed with the necessary orchestration in distributed scenarios involving embedded devices, actuators, controllers, and brokers at the network edge.
قيم البحث
اقرأ أيضاً
Network virtualization is a way to simultaneously run multiple heterogeneous architectures on a shared substrate. The main issue in the virtualization of networks is the problem of mapping virtual networks to the substrate network. How to manage subs
trate resources when performing the mapping will have an effective role in improving the use of infrastructure resources and consequently better mapping. By writing a module in the controller for dynamic resource management, an initial mapping has been attempted until the request arrives, if sufficient resources are available, but until the arrival of the n request that their initial mapping is successful, writing the rules in the switches is postponed. The simulation results with the NS2 simulator showed that compared to the two similar approaches, the proposed method could reduce the delay and the cost by maintaining the acceptance rate. Keywords: Heterogeneous, Network virtualization, Software-defined network, Virtual network mapping, Substrate Resources
Previous research on SDN traffic engineering mostly focuses on static traffic, whereas dynamic traffic, though more practical, has drawn much less attention. Especially, online SDN multicast that supports IETF dynamic group membership (i.e., any user
can join or leave at any time) has not been explored. Different from traditional shortest-path trees (SPT) and graph theoretical Steiner trees (ST), which concentrate on routing one tree at any instant, online SDN multicast traffic engineering is more challenging because it needs to support dynamic group membership and optimize a sequence of correlated trees without the knowledge of future join and leave, whereas the scalability of SDN due to limited TCAM is also crucial. In this paper, therefore, we formulate a new optimization problem, named Online Branch-aware Steiner Tree (OBST), to jointly consider the bandwidth consumption, SDN multicast scalability, and rerouting overhead. We prove that OBST is NP-hard and does not have a $|D_{max}|^{1-epsilon}$-competitive algorithm for any $epsilon >0$, where $|D_{max}|$ is the largest group size at any time. We design a $|D_{max}|$-competitive algorithm equipped with the notion of the budget, the deposit, and Reference Tree to achieve the tightest bound. The simulations and implementation on real SDNs with YouTube traffic manifest that the total cost can be reduced by at least 25% compared with SPT and ST, and the computation time is small for massive SDN.
This paper studies edge caching in fog computing networks, where a capacity-aware edge caching framework is proposed by considering both the limited fog cache capacity and the connectivity capacity of base stations (BSs). By allowing cooperation betw
een fog nodes and cloud data center, the average-download-time (ADT) minimization problem is formulated as a multi-class processor queuing process. We prove the convexity of the formulated problem and propose an Alternating Direction Method of Multipliers (ADMM)-based algorithm that can achieve the minimum ADT and converge much faster than existing algorithms. Simulation results demonstrate that the allocation of fog cache capacity and connectivity capacity of BSs needs to be balanced according to the network status. While the maximization of the edge-cache-hit-ratio (ECHR) by utilizing all available fog cache capacity is helpful when the BS connectivity capacity is sufficient, it is preferable to keep a lower ECHR and allocate more traffic to the cloud when the BS connectivity capacity is deficient.
Network Function Virtualization (NFV) on Software-Defined Networks (SDN) can effectively optimize the allocation of Virtual Network Functions (VNFs) and the routing of network flows simultaneously. Nevertheless, most previous studies on NFV focus on
unicast service chains and thereby are not scalable to support a large number of destinations in multicast. On the other hand, the allocation of VNFs has not been supported in the current SDN multicast routing algorithms. In this paper, therefore, we make the first attempt to tackle a new challenging problem for finding a service forest with multiple service trees, where each tree contains multiple VNFs required by each destination. Specifically, we formulate a new optimization, named Service Overlay Forest (SOF), to minimize the total cost of all allocated VNFs and all multicast trees in the forest. We design a new $3rho_{ST}$-approximation algorithm to solve the problem, where $rho_{ST}$ denotes the best approximation ratio of the Steiner Tree problem, and the distributed implementation of the algorithm is also presented. Simulation results on real networks for data centers manifest that the proposed algorithm outperforms the existing ones by over 25%. Moreover, the implementation of an experimental SDN with HP OpenFlow switches indicates that SOF can significantly improve the QoE of the Youtube service.
Many of the video streaming applications in todays Internet involve the distribution of content from a CDN source to a large population of interested clients. However, widespread support of IP multicast is unavailable due to technical and economical
reasons, leaving the floor to application layer multicast which introduces excessive delays for the clients and increased traffic load for the network. This paper is concerned with the introduction of an SDN-based framework that allows the network controller to not only deploy IP multicast between a source and subscribers, but also control, via a simple northbound interface, the distributed set of sources where multiple- description coded (MDC) video content is available. We observe that for medium to heavy network loads, relative to the state-of-the-art, the SDN-based streaming multicast video framework increases the PSNR of the received video significantly, from a level that is practically unwatchable to one that has good quality.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
