Xiaofei Liao

AnySee: Peer-to-Peer Live Streaming

Efficient and scalable live-streaming overlay construction has become a hot topic recently. In order to improve the performance metrics, such as startup delay, source-to-end delay, and playback continuity, most previous studies focused on intra-overlay optimization. Such approaches have drawbacks including low resource utilization, high startup and source-to-end delay, and unreasonable resource assignment in global P2P networks. Anysee is a peer-to-peer live streaming system and adopts an inter-overlay optimization scheme, in which resources can join multiple overlays, so as to (1) improve global resource utilization and distribute traffic to all physical links evenly; (2) assign resources based on their locality and delay; (3) guarantee streaming service quality by using the nearest peers, even when such peers might belong to different overlays; and (4) balance the load among the group members. We compare the performance of our design with existing approaches based on comprehensive trace driven simulations. Results show that AnySee outperforms previous schemes in resource utilization and the QoS of streaming services. AnySee has been implemented as an Internet based live streaming system, and was successfully released in the summer of 2004 in CERNET of China. Over 60,000 users enjoy massive entertainment programs, including TV programs, movies, and academic conferences. Statistics prove that this design is scalable and robust, and we believe that the wide deployment of AnySee will soon benefit many more Internet users.

Live migration of virtual machine based on full system trace and replay

Live migration of virtual machines (VM) across distinct physical hosts provides a significant new benefit for administrators of data centers and clusters. Previous migration schemes focused on transferring the runtime memory state of the VM. Those approaches employed memory pre-copy algorithm to synchronize the migrating VM states, which make VM live migration cost much network traffic and application downtime, especially for memory intensive workloads. This paper describes the design and implementation of a novel approach CR/TR-Motion that adopts checkpointing/recovery and trace/replay technology to provide fast, transparent VM migration. With execution trace logged on the source host, a synchronization algorithm is performed to orchestrate the running source and target VM until they get a consistent state. We also give a formalized characterization about the migration evaluation metrics and make a mathematical analysis about our algorithm. Our scheme can greatly reduce the migration downtime and network bandwidth consumption. Experimental measurements show that our approach can drastically reduce migration overheads compared with pre-copy algorithm: up to 72.4% on application observed downtime, up to 31.5% on total migration time and up to 95.9% on the data to synchronize the VM state, while the application performance overhead due to migration is less than 8.54% on average.

A Survey of Recent Developments in Home M2M Networks

Recent years have witnessed the emergence of machine-to-machine (M2M) networks as an efficient means for providing automated communications among distributed devices. Automated M2M communications can offset the overhead costs of conventional operations, thus promoting their wider adoption in fixed and mobile platforms equipped with embedded processors and sensors/actuators. In this paper, we survey M2M technologies for applications such as healthcare, energy management and entertainment. In particular, we examine the typical architectures of home M2M networks and discuss the performance tradeoffs in existing designs. Our investigation covers quality of service, energy efficiency and security issues. Moreover, we review existing home networking projects to better understand the real-world applicability of these systems. This survey contributes to better understanding of the challenges in existing M2M networks and further shed new light on future research directions.

Performance and energy modeling for live migration of virtual machines

Live migration of virtual machine (VM) provides a significant benefit for virtual server mobility without disrupting service. It is widely used for system management in virtualized data centers. However, migration costs may vary significantly for different workloads due to the variety of VM configurations and workload characteristics. To take into account the migration overhead in migration decision-making, we investigate design methodologies to quantitatively predict the migration performance and energy consumption. We thoroughly analyze the key parameters that affect the migration cost from theory to practice. We construct application-oblivious models for the cost prediction by using learned knowledge about the workloads at the hypervisor (also called VMM) level. This should be the first kind of work to estimate VM live migration cost in terms of both performance and energy in a quantitative approach. We evaluate the models using five representative workloads on a Xen virtualized environment. Experimental results show that the refined model yields higher than 90% prediction accuracy in comparison with measured cost. Model-guided decisions can significantly reduce the migration cost by more than 72.9% at an energy saving of 73.6%.

Live Virtual Machine Migration via Asynchronous Replication and State Synchronization

Live migration of virtual machines (VM) across physical hosts provides a significant new benefit for administrators of data centers and clusters. Previous memory-to-memory approaches demonstrate the effectiveness of live VM migration in local area networks (LAN), but they would cause a long period of downtime in a wide area network (WAN) environment. This paper describes the design and implementation of a novel approach, namely, CR/TR-Motion, which adopts checkpointing/recovery and trace/replay technologies to provide fast, transparent VM migration for both LAN and WAN environments. With execution trace logged on the source host, a synchronization algorithm is performed to orchestrate the running source and target VMs until they reach a consistent state. CR/TR-Motion can greatly reduce the migration downtime and network bandwidth consumption. Experimental results show that the approach can drastically reduce migration overheads compared with memory-to-memory approach in a LAN: up to 72.4 percent on application observed downtime, up to 31.5 percent on total migration time, and up to 95.9 percent on the data to synchronize the VM state. The application performance overhead due to migration is kept within 8.54 percent on average. The results also show that for a variety of workloads migrated across WANs, the migration downtime is less than 300 milliseconds.

Supporting VCR Functions in P2P VoD Services Using Ring-Assisted Overlays

Peer-to-peer (P2P) networks have been shown to be a promising approach to providing large-scale video-on-demand (VoD) services over the Internet for their potential scalability. However, how to efficiently support VCR functions for VoD services in such networks remains a major challenge. In this paper we propose a novel ring-assisted overlay topology, called RINDY, to address this issue. In RINDY, a peer can implement fast relocation of random seeks by maintaining some near neighbors and remote neighbors in a set of concentric rings with power law radii. We explore several key problems in RINDY including ring organization, neighbor placement over rings and neighbor lookup for random seeks. We evaluate its performance through simulations and compare it with some existing approaches. The experimental results show that RINDY outperforms previous schemes in terms of control overhead, latency and quality of streaming, especially under frequent VCR operations.

Magnet: A novel scheduling policy for power reduction in cluster with virtual machines

The concept of green computing has attracted much attention recently in cluster computing. However, previous local approaches focused on saving the energy cost of the components in a single workstation without a global vision on the whole cluster, so it achieved undesirable power reduction effect. Other cluster-wide energy saving techniques could only be applied to homogeneous workstations and specific applications. This paper describes the design and implementation of a novel approach that uses live migration of virtual machines to transfer load among the nodes on a multilayer ring-based overlay. This scheme can reduce the power consumption greatly by regarding all the cluster nodes as a whole. Plus, it can be applied to both the homogeneous and heterogeneous servers. Experimental measurements show that the new method can reduce the power consumption by 74.8% over base at most with certain adjustably acceptable overhead. The effectiveness and performance insights are also analytically verified.

GridCast: Improving peer sharing for P2P VoD

Video-on-Demand (VoD) is a compelling application, but costly. VoD is costly due to the load it places on video source servers. Many have proposed using peer-to-peer (P2P) techniques to shift load from servers to peers. Yet, nobody has implemented and deployed a system to openly and systematically evaluate how these techniques work. This article describes the design, implementation and evaluation of GridCast, a real deployed P2P VoD system. GridCast has been live on CERNET since May of 2006. It provides seek, pause, and play operations, and employs peer sharing to improve system scalability. In peak months, GridCast has served videos to 23,000 unique users. From the first deployment, we have gathered information to understand the system and evaluate how to further improve peer sharing through caching and replication. We first show that GridCast with single video caching (SVC) can decrease load on source servers by an average of 22% from a client-server architecture. We analyze the net effect on system resources and determine that peer upload is largely idle. This leads us to changing the caching algorithm to cache multiple videos (MVC). MVC decreases source load by an average of 51% over the client-server. The improvement is greater as user load increases. This bodes well for peer-assistance at larger scales. A detailed analysis of MVC shows that departure misses become a major issue in a P2P VoD system with caching optimization. Motivated by this observation, we examine how to use replication to eliminate departure misses and further reduce server load. A framework for lazy replication is presented and evaluated in this article. In this framework, two predictors are plugged in to create the working replication algorithm. With these two simple predictors, lazy replication can decrease server load by 15% from MVC with only a minor increase in network traffic.

Flash Crowd in P2P Live Streaming Systems: Fundamental Characteristics and Design Implications

Peer-to-peer (P2P) live video streaming systems have recently received substantial attention, with commercial deployment gaining increased popularity in the internet. It is evident from our practical experiences with real-world systems that, it is not uncommon for hundreds of thousands of users to choose to join a program in the first few minutes of a live broadcast. Such a severe flash crowd phenomenon in live streaming poses significant challenges in the system design. In this paper, for the first time, we develop a mathematical model to: 1) capture the fundamental relationship between time and scale in P2P live streaming systems under a flash crowd, and 2) explore the design principle of population control to alleviate the impact of the flash crowd. We carry out rigorous analysis that brings forth an in-depth understanding on effects of the gossip protocol and peer dynamics. In particular, we demonstrate that there exists an upper bound on the system scale with respect to a time constraint. By trading peer startup delays in the initial stage of a flash crowd for system scale, we design a simple and flexible population control framework that can alleviate the flash crowd without the requirement of otherwise costly server deployment.

Towards a green cluster through dynamic remapping of virtual machines

Since power is one of the major limiting factors for a data center or for large cluster growth, the objective of this study is to minimize the power consumption of the cluster without violating the performance constraints of the applications. We propose a runtime virtual machine (VM) mapping framework in a cluster or data center to save energy. The new framework can make reconfiguration decisions on time with the consideration of a low influence on the performance. In the GreenMap framework, one probabilistic, heuristic algorithm is designed for the optimization problem: mapping VMs onto a set of physical machines (PMs) under the constraint of multi-dimensional resource consumptions. Experimental measurements show that the new method can reduce the power consumption by up to 69.2% over base, with few performance penalties. The effectiveness and performance insights are also analytically verified.