22 research outputs found
Disaster-Resilient Control Plane Design and Mapping in Software-Defined Networks
Communication networks, such as core optical networks, heavily depend on
their physical infrastructure, and hence they are vulnerable to man-made
disasters, such as Electromagnetic Pulse (EMP) or Weapons of Mass Destruction
(WMD) attacks, as well as to natural disasters. Large-scale disasters may cause
huge data loss and connectivity disruption in these networks. As our dependence
on network services increases, the need for novel survivability methods to
mitigate the effects of disasters on communication networks becomes a major
concern. Software-Defined Networking (SDN), by centralizing control logic and
separating it from physical equipment, facilitates network programmability and
opens up new ways to design disaster-resilient networks. On the other hand, to
fully exploit the potential of SDN, along with data-plane survivability, we
also need to design the control plane to be resilient enough to survive network
failures caused by disasters. Several distributed SDN controller architectures
have been proposed to mitigate the risks of overload and failure, but they are
optimized for limited faults without addressing the extent of large-scale
disaster failures. For disaster resiliency of the control plane, we propose to
design it as a virtual network, which can be solved using Virtual Network
Mapping techniques. We select appropriate mapping of the controllers over the
physical network such that the connectivity among the controllers
(controller-to-controller) and between the switches to the controllers
(switch-to-controllers) is not compromised by physical infrastructure failures
caused by disasters. We formally model this disaster-aware control-plane design
and mapping problem, and demonstrate a significant reduction in the disruption
of controller-to-controller and switch-to-controller communication channels
using our approach.Comment: 6 page
Recursive SDN for Carrier Networks
Control planes for global carrier networks should be programmable (so that
new functionality can be easily introduced) and scalable (so they can handle
the numerical scale and geographic scope of these networks). Neither
traditional control planes nor new SDN-based control planes meet both of these
goals. In this paper, we propose a framework for recursive routing computations
that combines the best of SDN (programmability) and traditional networks
(scalability through hierarchy) to achieve these two desired properties.
Through simulation on graphs of up to 10,000 nodes, we evaluate our design's
ability to support a variety of routing and traffic engineering solutions,
while incorporating a fast failure recovery mechanism
Performance evaluation of caching techniques for video on demand workload in named data network
The rapid growing use of the Internet in the contemporary context is mainly for content
distribution. This is derived primarily due to the emergence of Information-Centric Networking (ICN) in the wider domains of academia and industry. Named Data Network (NDN) is one of ICN architectures. In addition, the NDN has been emphasized as the video traffic architecture that ensures smooth communication between the request and receiver of online video. The concise research problem of the current study is the issue of congestion in Video on Demand (VoD) workload caused by frequent storing of signed content object in the local repositories, which leads to buffering problems and data packet loss. The study will assess the NDN cache techniques to select the preferable cache replacement technique suitable for dealing with the congestion issues, and evaluate its performance. To do that, the current study adopts a research process based on the Design Research Methodology (DRM) and VoD approach in order to explain the main activities that produced an increase in the expected findings at the end of the activities or research. Datasets, as well as Internet2 network topology and the statistics of video views were gathered from the PPTV platform. Actually, a total of 221 servers is connected to the network from the same access points as in the real deployment
of PPTV. In addition, an NS3 analysis the performance metrics of caching replacement
technique (LRU, LFU, and FIFO) for VoD in Named Data Network (NDN) in terms of cache hit ratio, throughput, and server load results in reasonable outcomes that appears to serve as a potential replacement with the current implementation of the Internet2 topology, where nodes are distributed randomly. Based on the results, LFU technique gives the preferable result for congestion from among the presented
techniques. Finally, the research finds that the performance metrics of cache hit ratio,
throughput, and server load for the LFU that produces the lowest congestion rate which
is sufficient. Therefore, the researcher concluded that the efficiency of the different replacement techniques needs to be well investigated in order to provide the insights
necessary to implement these techniques in certain context. However, this result enriches
the current understanding of replacement techniques in handling different cache sizes. After having addressed the different replacement techniques and examined their
performances, the performance characteristics along with their expected performance were also found to stimulate a cache model for providing a relatively fast running time of across a broad range of embedded applications
Performance evaluation of caching placement algorithms in named data network for video on demand service
The purpose of this study is to evaluate the performance of caching placement algorithms
(LCD, LCE, Prob, Pprob, Cross, Centrality, and Rand) in Named Data Network (NDN) for Video on Demand (VoD). This study aims to increment the service quality and to decrement the time of download. There are two stages of activities resulted in the outcome of the study: The first is to determine the causes of delay performance
in NDN cache algorithms used in VoD workload. The second activity is the evaluation of the seven cache placement algorithms on the cloud of video content in terms of the key performance metrics: delay time, average cache hit ratio, total reduction in the network footprint, and reduction in load. The NS3 simulations and the Internet2 topology were used to evaluate and analyze the findings of each algorithm, and to compare the results based on cache sizes: 1GB, 10GB, 100GB, and 1TB. This study proves that the different user requests of online videos would lead to delay in network performance. In addition to that the delay also caused by the high increment of video
requests. Also, the outcomes led to conclude that the increase in cache capacity leads
to make the placement algorithms have a significant increase in the average cache hit
ratio, a reduction in server load, and the total reduction in network footprint, which resulted in obtaining a minimized delay time. In addition to that, a conclusion was made
that Centrality is the worst cache placement algorithm based on the results obtained
A Review on Cache Replacement Strategies in Named Data Network
Named Data Network (NDN) architecture is one of the newest and future-aspired Internet communication systems. Video-on-Demand (VoD) has rapidly emerged as a popular online service. However, it is costly, considering its high bandwidth and popularity. Internet on-demand video traffic has been growing quite fast, and on-demand video streaming has gained much attention. The problem of this study is that the NDN architecture is processing several forms of online video requests simultaneously. However, limited cache and multiple buffering of requested videos result in loss of data packet as a consequence of the congestion in the cache storage network. Addressing this problem is essential as congestion cause network instability. This work emphasizes on the review of cache replacement strategies to deal with the congestion issue in Named Data Networks (NDN) during the VoD delivery in order to determine the performance (strengths and weaknesses) of the cache replacement strategies. Finally, this study proposes the replacement strategies must be enhanced with a new strategy that depends on popularity and priority regarding the congestion. This study would positively benefits both suppliers and users of Internet videos
TEL: Low-Latency Failover Traffic Engineering in Data Plane
Modern network applications demand low-latency traffic engineering in the
presence of network failure while preserving the quality of service constraints
like delay and capacity. Fast Re-Route (FRR) mechanisms are widely used for
traffic re-routing purposes in failure scenarios. Control plane FRR typically
computes the backup forwarding rules to detour the traffic in the data plane
when the failure occurs. This mechanism could be computed in the data plane
with the emergence of programmable data planes. In this paper, we propose a
system (called TEL) that contains two FRR mechanisms, namely, TEL-C and TEL-D.
The first one computes backup forwarding rules in the control plane, satisfying
max-min fair allocation. The second mechanism provides FRR in the data plane.
Both algorithms require minimal memory on programmable data planes and are
well-suited with modern line rate match-action forwarding architectures (e.g.,
PISA). We implement both mechanisms on P4 programmable software switches (e.g.,
BMv2 and Tofino) and measure their performance on various topologies. The
obtained results from a datacenter topology show that our FRR mechanism can
improve the flow completion time up to 4.6x7.3x (i.e., small flows) and
3.1x12x (i.e., large flows) compared to recirculation-based mechanisms, such
as F10, respectively
Randomized Local Fast Rerouting for Datacenter Networks with Almost Optimal Congestion
To ensure high availability, datacenter networks must rely on local fast
rerouting mechanisms that allow routers to quickly react to link failures, in a
fully decentralized manner. However, configuring these mechanisms to provide a
high resilience against multiple failures while avoiding congestion along
failover routes is algorithmically challenging, as the rerouting rules can only
depend on local failure information and must be defined ahead of time. This
paper presents a randomized local fast rerouting algorithm for Clos networks,
the predominant datacenter topologies. Given a graph describing a
Clos topology, our algorithm defines local routing rules for each node , which only depend on the packet's destination and are conditioned on the
incident link failures. We prove that as long as number of failures at each
node does not exceed a certain bound, our algorithm achieves an asymptotically
minimal congestion up to polyloglog factors along failover paths. Our lower
bounds are developed under some natural routing assumptions