Chang-Gun Lee

MMSPEED: multipath Multi-SPEED protocol for QoS guarantee of reliability and. Timeliness in wireless sensor networks

In this paper, we present a novel packet delivery mechanism called Multi-Path and Multi-SPEED Routing Protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. These mechanisms for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates for local decision inaccuracies as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements up to 50 percent (12 flows versus 18 flows).

Probabilistic QoS guarantee in reliability and timeliness domains in wireless sensor networks

In this paper, we present a novel packet delivery mechanism called multi-path and multi-speed routing protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. All these for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates the local decision inaccuracy as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements.

Partitioning based mobile element scheduling in wireless sensor networks

In recent studies, using mobile elements (MEs) as mechanical carriers of data has been shown to be an effective way of prolonging sensor network life time and relaying information in partitioned networks. As the data generation rates of sensors may vary, some sensors need to be visited more frequently than others. In this paper, a partitioning-based algorithm is presented that schedules the movements of MEs in a sensor network such that there is no data loss due to buffer overflow. Simulation results show that the proposed Partitioning Based Scheduling (PBS) algorithm performs well in terms of reducing the minimum required ME speed to prevent data loss, providing high predictability in inter-visit durations, and minimizing the data loss rate for the cases when the ME is constrained to move slower than the minimum required ME speed.

CHARACTERIZING VOICE AND VIDEO TRAFFIC BEHAVIOR OVER THE INTERNET

In this paper, we present our research on characterizing voice and video traffic behavior in large-scale Internet Videoconferencing systems. We built a voice and video traffic quality measurement testbed to collect Videoconferencing traffic traces from several sites all over the world that were connected to our testbed via disparate network paths on the Internet. Our testbed also featured the H.323 Beacon, an H.323 session performance assessment tool we have developed, and various other open-source and commercial tools. Our findings obtained by analyzing the collected traffic traces demonstrate the impact of: 1) end-point technologies that use popular audio and video codecs and 2) network health status that is characterized by the variations of delay, jitter, lost and reordered packets in the network, on the end-user perception of audiovisual quality. The perceptual data used in our analysis includes both objective and subjective quality measures. These measures were collected from our testbed experiments for a few sample tasks involving various levels of human interaction in Internet Videoconferences.

Enhanced EDF scheduling algorithms for orchestrating network-wide active measurements

Monitoring network status such as end-to-end delay, jitter, and available bandwidth is important to support QoS-sensitive applications and timely detection of network anomalies like denial of service attacks. For this purpose, Internet service providers (ISPs) have started to instrument their networks with network measurement infrastructures (NMIs) that periodically run active measurement tasks using measurement servers located at strategic points in their networks. However, one problem that most network engineers have overlooked is the measurement conflict problem. Since active measurement tasks actively inject test packets to collect measurements along network paths, running multiple active measurements at the same time over the same path could result in misleading reports of network performance. We call this phenomenon a measurement conflict. Our recent observation of such measurement conflict motivates us to form a measurement task scheduling problem of meeting periodicity requirements, where real-time scheduling algorithms can play a role. The scheduling problem, however, is not exactly same as any of the existing scheduling problems in the realtime literature, because the problem involves multiple measurement servers running multiple measurement tasks whose conflict dependency propagates along the chains of paths. For this problem, we propose to use an EDF (earliest deadline first) heuristic but allowing concurrent executions if possible, to construct an offline schedule for a given measurement task set. Also, we propose a novel mechanism to flexibly use the offline schedule for minimizing the response time of dynamic on-demand measurement jobs. Further, we implement and deploy our scheduling algorithms in a real working NMI for monitoring Internet 2 Abilene network

Orchestration of Network-Wide Active Measurements for Supporting Distributed Computing Applications

Recent computing applications such as videoconferencing and grid computing run their tasks on distributed computing resources connected through networks. For such applications, knowledge of the network status such as delay, jitter, and available bandwidth can help them select proper network resources to meet the Quality-of-Service (QoS) requirements. Also, the applications can dynamically change the resource selection if the current selection is found to experience poor performance. For such purposes, Internet Service Providers (ISPs) have started to instrument their networks with Network Measurement Infrastructures (NMIs) that run active measurement tasks periodically and/or on demand. However, one problem that most network engineers have overlooked is the measurement conflict problem, which happens when multiple active measurement tasks inject probing packets into the same network segment at the same time, resulting in misleading reports of network performance due to their combined effects. This paper proposes enhanced Earliest Deadline First (EDF) algorithms that allow Concurrent Executions to orchestrate offline/online measurement jobs in a conflict-free manner. The simulation study shows that our measurement scheduling mechanism can improve the schedulable utilization of offline measurement tasks up to 300 percent and the response time of on-demand jobs up to 50 percent. Further, we implement and deploy our scheduling mechanism in a real working NMI for monitoring the Internet2 Abilene network. As a case study, we show the utility of our algorithms in the widely used Network Weather Service (NWS).

Measuring Interaction QoE in Internet Videoconferencing

Internet videoconferencing has emerged as a viable medium for communication and entertainment. However, its widespread use is being challenged. This is because videoconference end-users frequently experience perceptual quality impairments such as video frame freezing and voice dropouts due to changes in network conditions on the Internet. These impairments cause extra end-user interaction effortand correspondingly lead to unwanted network bandwidth consumptionthat affects user Quality of Experience (QoE) and Internet congestion. Hence, it is important to measure and subsequently minimize the extra end-user interaction effort in a videoconferencing system. In this paper, we describe a novel active measurement scheme that considers end-user interaction effort and the corresponding network bandwidth consumption to provide videoconferencing interaction QoE measurements. The scheme involves a Multi-Activity Packet-Trains (MAPTs) methodology to dynamically emulate a videoconference sessions participant interaction patterns and corresponding video activity levels that are affected by transient changes in network conditions. Also, we describe the implementation and validation of the Vperftool we have developed to measure the videoconferencing interaction QoE on a network path using our proposed scheme.

Ontimemeasure: a scalable framework for scheduling active measurements

In order to satisfy and maintain service level agreements (SLAs), which demand high network availability and good network health, ISPs have started instrumenting their networks with network measurement infrastructures (NMIs) that are composed of dedicated measurement servers. Active measurements are frequently used in NMIs to regularly monitor network health and analyze the experience of end-user application traffic traversing the network. However, active measurements initiated by measurement servers need to be regulated. Unregulated active measurement traffic can cause an unpredictable negative impact on the actual application traffic. Also, running simultaneous conflicting active measurements on measurement servers could result in misleading reports of network performance. In this paper, we describe our active measurements scheduling framework called OnTimeMeasure that allows ISPs to regulate the amount of active measurement traffic injected into the network and also prevents conflicts in ongoing active measurements between measurement servers. OnTimeMeasure provides a simple scripting language interface to specify various measurement requirements such as physical topology of measurement server clusters, periodicity of the measurements, and properties of measurement tools. For a given measurement requirements script, OnTimeMeasure uses an efficient heuristic bin-packing algorithm to generate measurement timetables for orchestrating active measurements for a network involving multiple measurement servers, each hosting multiple measurement tools.

Ontology-Based Semantic Priority Scheduling for Multi-domain Active Measurements

Network control and management techniques (e.g., dynamic path switching and on-demand bandwidth provisioning) rely on active measurements of the end-to-end network status. The measurements are needed to meet network monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. Recent widespread deployment of openly accessible multi-domain active measurement frameworks, such as perfSONAR, has resulted in users competing for system and network measurement resources. Hence, there is a need to prioritize measurement requests of users before they are scheduled on measurement resources. In this paper, we present a novel ontology-based semantic priority scheduling algorithm (SPS) that handles resource contention while servicing measurement requests for meeting network monitoring objectives. We adopt ontologies to formalize semantic definitions and develop an inference engine to dynamically prioritize measurement requests. The prioritization is based upon user roles, user sampling preferences, resource policies, and oversampling mitigation factors. Performance evaluation results demonstrate that our SPS algorithm outperforms existing deterministic and heuristic algorithms in terms of user ‘satisfaction ratio’ and ‘average stretch’ among serviced measurement requests. Further, by sampling experiments on real-network perfSONAR measurement data sets, we show that our SPS algorithm successfully mitigates oversampling and further improves the satisfaction ratio. Our SPS scheme and evaluation results are vital to manage large-scale measurement infrastructures used for meeting monitoring objectives in the next-generation applications and networks.

Real time guarantee of aperiodic packets in single hop ad hoc wireless networks

Building real-time applications on 802.11 wireless networks is challenging because the medium access protocol is distributed and nodes contend for the channel nondeterministically. So far all attempts at providing real-time services in 802.11 require restrictive traffic assumptions such as periodicity. In this paper we describe distributed admission control, a modification to 802.11 that, when used with distributed prioritization, provides real-time guarantees for aperiodic packets. We show that barring external errors such as interference on the channel or incorrect priority scheduling this protocol guarantees deadlines will be met.