Jiaqi Zheng, Qiufang Ma, Chen Tian, Bo Li, Haipeng Dai, Hong Xu, Guihai Chen, Q. Ni
{"title":"Hermes: Utility-Aware Network Update in Software-Defined WANs","authors":"Jiaqi Zheng, Qiufang Ma, Chen Tian, Bo Li, Haipeng Dai, Hong Xu, Guihai Chen, Q. Ni","doi":"10.1109/ICNP.2018.00032","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00032","url":null,"abstract":"State-of-the-art inter-datacenter WANs rely on software defined networking (SDN) to orchestrate their data transmission. Optimization requires frequent network update operations to switch forwarding tables. When scheduling inter-datacenter WANs, the utility of services should be respected. Yet, existing network update approaches do not respect network utility and could result in performance degradation during the network update procedure. Further, the update causes not only performance degradation, but also the degradation period is unnecessarily prolonged. In this paper we propose Hermes, a utility-aware network update system. We aim to find a rate limiting scheme for update which maximizes the sum of service utility, while ensuring the congestion-free property during the update. We propose an optimization framework for the maximum utility network update problem (MUP). MUP is NP-hard and a series of algorithms are developed to solve it. Extensive simulation and testbed experiments with a prototype demonstrate that Hermes can increase the total utility by 80% compared to state-of-the-art. At the same time, it reduces the total update time and control overhead by 40% and 55%, respectively.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131221108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vitalii Demianiuk, S. Nikolenko, P. Chuprikov, Kirill Kogan
{"title":"New Alternatives to Optimize Policy Classifiers","authors":"Vitalii Demianiuk, S. Nikolenko, P. Chuprikov, Kirill Kogan","doi":"10.1109/ICNP.2018.00022","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00022","url":null,"abstract":"Growing expressiveness of services increases the size of a manageable state at the network data plane. A service policy is an ordered set of classification patterns (classes) with actions; the same class can appear in multiple policies. Previous studies mostly concentrated on efficient representations of a single policy instance. In this work, we study space efficiency of multiple policies, cutting down a classifier size by sharing instances of classes between policies that contain them. In this paper we identify conditions for such sharing, propose efficient algorithms and analyze them analytically. The proposed representations can be deployed transparently on existing packet processing engines. Our results are supported by extensive evaluations.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132672089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Kiram and WOE: Distributed Denial of Service Attacks in Named-Data Networking","authors":"Mohibi Hussain, J. Crowcroft","doi":"10.1109/ICNP.2018.00040","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00040","url":null,"abstract":"The current Internet infrastructure, initially conceived to provide closed group connectivity to a limited user-base, is now facing the challenges of catering to over three billion users with dynamically changing data, transport, and access requirements. Content-Centric Networking (CCN) is being explored as a possible future Internet architecture. Named-Data Networking (NDN) exemplifies CCN and with the ever-changing security landscape, it is imperative to build it with intrinsic resilience based on the security by design narrative. In this extended abstract, we explore the fake interest fiooding by adversaries to launch a Distributed Denial of Service (DDoS) attack in NDN. We propose Kiram as an intelligent anomaly recognition and alert generation mechanism serving as a collaborative countermeasure to a DDoS attack. The alert generated by Kiram is named Warding Off Evil (WOE). This poster presents results establishing the effectiveness of Kiram based on substantial simulations over a fairly realistic topology.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133692651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IoTm: A Lightweight Framework for Fine-Grained Measurements of IoT Performance Metrics","authors":"Muhammad Shahzad, Anirudh Ganji","doi":"10.1109/ICNP.2018.00012","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00012","url":null,"abstract":"Most Internet of Things (IoT) applications require unique guarantees on various performance metrics (such as latency, CPU availability, power fairness, etc.) from the IoT infrastructure. A small deterioration in these performance metrics can cause serious violations of service level agreements. To ensure that the deployed IoT infrastructure delivers the guarantees on these metrics, the first step is to measure these metrics. We present IoTm, a framework for measuring IoT performance metrics, which include both IoT network's quality of service (QoS) metrics and IoT node's resource utilization (RU) metrics. IoTm has two key properties: 1) it is lightweight and thus amenable for implementation on resource constrained IoT nodes; and 2) it can perform measurements at fine-grained levels and not just at aggregate levels. IoTm is comprised of two components, a lightweight IoT node unit (INU), which resides in each of the IoT nodes, and a control and query unit (CQU), which resides in a logically centralized management server. The primary role of INU is to record appropriate information about the desired performance metrics in the IoT nodes. To record the information, INU leverages a generic data structure that we propose. CQU is responsible for identifying the metrics and the IoT nodes on which those metrics should be monitored to achieve a desired measurement objective. CQU also stores the copies of data structures that the INU sends to it for long term storage. Both INU and CQU further contain query processing engines, which operate on the information stored in the data structures to answer measurement queries. To demonstrate the use of our framework, we apply it to one RU metric (number of disk accesses), and one QoS metric (round trip latency), and evaluate its accuracy. We also analyze the feasibility of its implementation on IoT nodes in terms of memory requirement and computational complexity.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124452030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chanhee Lee, Changhoon Yoon, Seungwon Shin, S. Cha
{"title":"INDAGO: A New Framework For Detecting Malicious SDN Applications","authors":"Chanhee Lee, Changhoon Yoon, Seungwon Shin, S. Cha","doi":"10.1109/ICNP.2018.00031","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00031","url":null,"abstract":"Software-Defined Networking (SDN) controllers not only provide centralized control of SDNs, but also implement open and programmable APIs to ultimately establish an open network environment, where anyone can develop and deliver useful SDN applications. In such an environment, malicious SDN applications can be easily developed and distributed by untrusted entities and can even possess full control of SDNs. Thus, the security threat of malicious SDN applications must be taken seriously. In this paper, we propose a novel system, called Indago, which statically analyzes SDN applications to model their behavioral profiles, and finally, it automatically detects malicious SDN applications with a machine learning approach. We implement a prototype system and evaluate its effectiveness with real world SDN applications and malware. Our evaluation results show that the system can detect most known SDN malware with a high detection rate and low error rates.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133719264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ashkan Aghdai, Mark Huang, David H. Dai, Yang Xu, H. J. Chao
{"title":"Transparent Edge Gateway for Mobile Networks","authors":"Ashkan Aghdai, Mark Huang, David H. Dai, Yang Xu, H. J. Chao","doi":"10.1109/ICNP.2018.00057","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00057","url":null,"abstract":"Advances in software-defined networking (SDN) enable a wave of innovation in a wide selection of networks ranging from data center networks to WAN. While existing standard bodies for mobile networks define stringent requirements, they too are embracing the flexibility of SDN in defining the specifications of the next generation of mobile networks. Mobile edge computing (MEC), in particular, is an emerging architecture to bring virtualized network functions and programmable network devices closer to the user. For instance, delay-sensitive or bandwidth-hungry computing resources are moved to the edge of the radio access network (RAN) to provide low latency computation and/or content for users while alleviating the backhaul pressure for network operators. In this paper, we propose an edge gateway (EGW) in the MEC that enables offloading of computation and storage resources to the edge of mobile networks. The EGW is backward compatible with components and protocols of LTE networks and does not require any modification in the user equipment, LTE software, or offloaded resources. We have designed and implemented the EGW using P4 language and verified its operation on a small testbed using a low-end P4 target and a reference LTE protocol stack.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127902529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Walid A. Y. Aljoby, Xin Wang, T. Fu, Richard T. B. Ma
{"title":"On SDN-Enabled Online and Dynamic Bandwidth Allocation for Stream Analytics","authors":"Walid A. Y. Aljoby, Xin Wang, T. Fu, Richard T. B. Ma","doi":"10.1109/ICNP.2018.00030","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00030","url":null,"abstract":"Data communication in cloud-based distributed stream data analytics often involves a collection of parallel and pipelined TCP flows. As the standard TCP congestion control mechanism is designed for achieving \"fairness\" among competing flows and is agnostic to the application layer contexts, the bandwidth allocation among a set of TCP flows traversing bottleneck links often leads to sub-optimal application-layer performance measures, e.g., stream processing throughput or average tuple complete latency. Motivated by this and enabled by the rapid development of the Software-Defined Networking (SDN) techniques, in this paper, we re-investigate the design space of the bandwidth allocation problem and propose a cross-layer framework which utilizes the additional information obtained from the application layer and provides on-the-fly and dynamic bandwidth adjustment algorithms for helping the stream analytics applications achieving better performance during the runtime. We implement a prototype cross-layer bandwidth allocation framework based on a popular open-source distributed stream processing platform, Apache Storm, together with the OpenDaylight controller, and carry out extensive experiments with real-world analytical workloads on top of a local cluster consisting of 10 workstations interconnected by a SDN-enabled switch. The experiment results clearly validate the effectiveness and efficiency of our proposed framework and algorithms.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127627334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Changfu Lin, Jingjing Zhan, Hanhua Chen, Jie Tan, Hai Jin
{"title":"Ares: A High Performance and Fault-Tolerant Distributed Stream Processing System","authors":"Changfu Lin, Jingjing Zhan, Hanhua Chen, Jie Tan, Hai Jin","doi":"10.1109/ICNP.2018.00027","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00027","url":null,"abstract":"Distributed Stream Processing Systems (DSPSs) have been widely deployed to process infinite data streams. Short processing latency and short recovery time are both vital for many DSPS applications. Existing DSPS designs commonly leverage elaborated task allocation strategies to achieve short processing latency. Such designs, however, ignore the requirement of system fault tolerance. Indeed, providing fault tolerant capability in a DSPS can cause significant degradation of system performance. Especially, the intrinsic dependency between upstream and down-stream tasks can incur cascaded waiting during recovery, leading to prohibitively long recovery time. In this paper, we propose Ares, a high performance and fault tolerant DSPS. Ares considers both system performance and fault tolerant capability during task allocation. In the design of Ares, we formalize the problem of Fault Tolerant Scheduler (FTS) for finding an optimal task allocation which maximizes the system utility. We use a game-theoretic approach to solve the FTS problem and propose a novel Nirvana algorithm based on best-response dynamics. We mathematically prove the existence of Nash equilibrium in the FTS game. We implement Ares atop Apache Storm and conduct comprehensive experiments to evaluate this design. The results show that, compared to existing designs Ares achieves a 3.6× improvement of throughput, as well as reducing the processing latency and the recovery time by 50.2% and 52.5%, respectively.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121072539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"DCQCN+: Taming Large-Scale Incast Congestion in RDMA over Ethernet Networks","authors":"Yixiao Gao, Yuchen Yang, Chen Tian, Jiaqi Zheng, Bing Mao, Guihai Chen","doi":"10.1109/ICNP.2018.00021","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00021","url":null,"abstract":"Remote Direct Memory Access (RDMA) gains growing popularity in datacenter networks. The state-of-the-art congestion control scheme is DCQCN. However, DCQCN has performance problems when large-scale incast communication happens. DCQCN uses fixed period and steps for rate increase when probing for available bandwidth and this scheme is not scalable. Our key insight is that: senders should be aware of the scale of each incast, so that they can adjust their aggressiveness accordingly. The challenges come from different aspects. The scale of congestion is not easy to estimate while the control scheme should be cautiously designed. In this paper, we propose DCQCN+ to improve performance for large-scale incast congestion in RDMA networks. DCQCN+ adapts the rate control mechanisms to different scenarios. DCQCN+ can deal with incast congestion of at least 2,000 flows both in simulation and testbed. The scale is 10 times larger than that of DCQCN in simulation and 4 times larger in testbed. DCQCN+ also has 10 times smaller latency.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129038658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chavoosh Ghasemi, Hamed Yousefi, K. Shin, Beichuan Zhang
{"title":"A Fast and Memory-Efficient Trie Structure for Name-Based Packet Forwarding","authors":"Chavoosh Ghasemi, Hamed Yousefi, K. Shin, Beichuan Zhang","doi":"10.1109/ICNP.2018.00046","DOIUrl":"https://doi.org/10.1109/ICNP.2018.00046","url":null,"abstract":"Name lookup is an essential function, but a performance bottleneck in both today's and future network architectures. Variable-length and unbounded names rather than fixed-length addresses, as well as much larger and more dynamic forwarding tables call for a careful re-engineering of lookup structures for fast, memory-efficient, and scalable packet forwarding. We propose a novel data structure, called NameTrie, to store and index forwarding table entries efficiently and to support fast name lookups and updates. Its novelty lies in the optimized design and implementation of a character-trie structure. The nodes of NameTrie are stored compactly, improving cache efficiency and speeding up packet processing. Its edges are implemented using a hash table, facilitating fast name lookups and updates. A new scheme is used to encode control information without consuming additional memory. Running on conventional commodity hardware and using large-scale real-world name datasets, our implementation of NameTrie in software achieves 2.82~3.56, 3.48~3.72, and 2.73~3.25 million name insertions, lookups, and removals per second, respectively, for various datasets while requiring a small memory footprint. We have conducted a comprehensive performance evaluation against the state-of-the-art of named data networking (NDN) as a typical use-case. It is shown to require at least 35% less memory and runs at least 3x faster for name table lookups and updates than two well-known trie-based schemes in NDN.","PeriodicalId":264202,"journal":{"name":"2018 IEEE 26th International Conference on Network Protocols (ICNP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117019060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}