Do you want to publish a course? Click here

Contra: A Programmable System for Performance-aware Routing

59   0   0.0 ( 0 )
 Added by Kuo-Feng Hsu
 Publication date 2019
and research's language is English
 Authors Kuo-Feng Hsu




Ask ChatGPT about the research

We present Contra, a system for performance-aware routing that can adapt to traffic changes at hardware speeds. While existing work has developed point solutions for performance-aware routing on a fixed topology (e.g., a Fattree) with a fixed routing policy (e.g., use least utilized paths), Contra can be configured to operate seamlessly over any network topology and a wide variety of sophisticated routing policies. Users of Contra write network-wide policies that rank network paths given their current performance. A compiler then analyzes such policies in conjunction with the network topology and decomposes them into switch-local P4 programs, which collectively implement a new, specialized distance-vector protocol. This protocol generates compact probes that traverse the network, gathering path metrics to optimize for the user policy dynamically. Switches respond to changing network conditions at hardware speeds by routing flowlets along the best policy-compliant paths. Our experiments show that Contra scales to large networks, and that in terms of flow completion times, it is competitive with hand-crafted systems that have been customized for specific topologies and policies.



rate research

Read More

Bring Your Own Device (BYOD) has become the new norm in enterprise networks, but BYOD security remains a top concern. Context-aware security, which enforces access control based on dynamic runtime context, holds much promise. Recent work has developed SDN solutions to collect device context for network-wide access control in a central controller. However, the central controller poses a bottleneck that can become an attack target, and processing context changes at remote software has low agility. We present a new paradigm, programmable in-network security (Poise), which is enabled by the emergence of programmable switches. At the heart of Poise is a novel switch primitive, which can be programmed to support a wide range of context-aware policies in hardware. Users of Poise specify concise policies, and Poise compiles them into different instantiations of the security primitive in P4. Compared to centralized SDN defenses, Poise is resilient to control plane saturation attacks, and it dramatically increases defense agility.
Wireless medium access control (MAC) and routing protocols are fundamental building blocks of the Internet of Things (IoT). As new IoT networking standards are being proposed and different existing solutions patched, evaluating the end-to-end performance of the network becomes challenging. Specific solutions designed to be beneficial, when stacked may have detrimental effects on the overall network performance. In this paper, an analysis of MAC and routing protocols for IoT is provided with focus on the IEEE 802.15.4 MAC and the IETF RPL standards. It is shown that existing routing metrics do not account for the complex interactions between MAC and routing, and thus novel metrics are proposed. This enables a protocol selection mechanism for selecting the routing option and adapting the MAC parameters, given specific performance constraints. Extensive analytical and experimental results show that the behavior of the MAC protocol can hurt the performance of the routing protocol and vice versa, unless these two are carefully optimized together by the proposed method.
Reactive routing protocols are gaining popularity due to their event driven nature day by day. In this vary paper, reactive routing is studied precisely. Route request, route reply and route maintenance phases are modeled with respect to control overhead. Control overhead varies with respect to change in various parameters. Our model calculates these variations as well. Besides modeling, we chose three most favored reactive routing protocols as Ad-Hoc on Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Dynamic MANET on Demand (DYMO) for our experiments. We simulated these protocols using ns-2 for a detailed comparison and performance analysis with respect to mobility and scalability issues keeping metrics of throughput, route delay and control over head. Their performances and comparisons are extensively presented in last part of our work.
417 - D. Mahmood , N. Javaid , U. Qasim 2013
To ensure seamless communication in wireless multi-hop networks, certain classes of routing protocols are defined. This vary paper, is based upon proactive routing protocols for Wireless multihop networks. Initially, we discuss Destination Sequence Distance Vector (DSDV), Fish-eye State Routing (FSR) and Optimized Link State Routing (OLSR), precisely followed by mathematical frame work of control overhead regarding proactive natured routing protocols. Finally, extensive simulations are done using NS 2 respecting above mentioned routing protocols covering mobility and scalability issues. Said protocols are compared under mobile and dense environments to conclude our performance analysis.
189 - Boyu Diao , Chao Li , Qi Wang 2021
The underwater acoustic channel is one of the most challenging communication channels. Due to periodical tidal and daily climatic variation, underwater noise is periodically fluctuating, which result in the periodical changing of acoustic channel quality in long-term. Also, time-variant channel quality leads to routing failure. Routing protocols with acoustic channel estimation, namely underwater channel-aware routing protocols are recently proposed to maintain the routing performance. However, channel estimation algorithms for these routing protocols are mostly linear and rarely consider periodicity of acoustic channels. In this paper, we introduce acoustic channel estimation based on nearest neighbor regression for underwater acoustic networks. We extend nearest neighbor regression for SNR (Signal-to-Noise Ratio) time series prediction, providing an outstanding prediction accuracy for intricately periodical and fluctuating received SNR time series. Moreover, we propose a quick search algorithm and use statistical storage compression to optimize the time and space complexity of the algorithm. In contrast with linear methods, this algorithm significantly improves channel prediction accuracy (over three times at most) on both simulation and sea trial data sets. With this channel estimation method, we then propose a Depth-Based Channel-Aware Routing protocol (DBCAR). Taking advantage of depth-greedy forwarding and channel-aware reliable communication, DBCAR has an outstanding network performance on packet delivery ratio, average energy consumption and average transmission delay which is validated through extensive simulations.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا