Wu-Chun Chung

JackHare: a framework for SQL to NoSQL translation using MapReduce

As data exploration has increased rapidly in recent years, the datastore and data processing are getting more and more attention in extracting important information. To find a scalable solution to process the large-scale data is a critical issue in either the relational database system or the emerging NoSQL database. With the inherent scalability and fault tolerance of Hadoop, MapReduce is attractive to process the massive data in parallel. Most of previous researches focus on developing the SQL or SQL-like queries translator with the Hadoop distributed file system. However, it could be difficult to update data frequently in such file system. Therefore, we need a flexible datastore as HBase not only to place the data over a scale-out storage system, but also to manipulate the changeable data in a transparent way. However, the HBase interface is not friendly enough for most users. A GUI composed of SQL client application and database connection to HBase will ease the learning curve. In this paper, we propose the JackHare framework with SQL query compiler, JDBC driver and a systematical method using MapReduce framework for processing the unstructured data in HBase. After importing the JDBC driver to a SQL client GUI, we can exploit the HBase as the underlying datastore to execute the ANSI-SQL queries. Experimental results show that our approaches can perform well with efficiency and scalability.

A Novel Approach for Cooperative Overlay-Maintenance in Multi-overlay Environments

Overlay networks are widely adopted in many distributed systems for efficient resource sharing. Recently, issues in overlay network have also been introduced into cloud systems, in order to organize thousands of virtualized resources. In parallel, the explosion of P2P applications introduces the multi-overlay environment in which a number of nodes simultaneously participate in multiple overlays. When multiple applications running over a large set of nodes, some of nodes may take repeated efforts to preserve multi-overlay networks. Therefore, maintaining these co-existing overlays brings the redundant maintenance overhead. This paper presents a cooperative strategy to analyze the overlay maintenance of multi-overlay environments and to elaborate multiple overlays for simplifying the overlay maintenance. The proposed strategy exploits the synergy of co-existing overlays to handle their common overlay-maintenance, so that the redundant maintenance overhead could be eliminated while keeping performance. To evaluate the system performance, this paper not only analyzes several overlays but also considers realistic multi-overlay environments by varying the intersection ratio of diverse overlays and the combination of multiple overlays. Experimental results show that the proposed cooperative strategy significantly decreases the redundant overlay-maintenance overhead, where the reduction ratio of maintaining multiple overlays is higher than 60 percent in some of cases.

Minimizing Latency of Real-Time Container Cloud for Software Radio Access Networks

As the huge growth of mobile traffic amount, conventional Radio Access Networks (RANs) suffer from high capital and operating expenditures, especially when new cellular standards are deployed. Software, and cloud RANs have been proposed, but the stringent latency requirements e.g., 1 ms transmission time interval, dictated by cellular networks is difficult to satisfy. We first present a real software RAN testbed based on an opensource LTE implementation. We also investigate the issue of quality assurance when deploying such software RANs in cloud. In particular, running software RANs in cloud leads to high latency, which may violate the latency requirements. We empirically study the problem of minimizing computational and networking latencies in lightweight container cloud. Our experiment results show the feasibility of running software RANs in real-time container cloud. More specifically, a feasible solution to host software RANs in cloud is to adopt lightweight containers with real-time kernels and fast packet processing networking.

Direction-aware resource discovery in large-scale distributed computing environments

As a system scales up, the peer-to-peer (P2P) approach is attractive to distributed computing environments, such as Grids and Clouds, due to the amount of resources increased. The major issue in large-scale distributed systems is to prevent the phenomenon of a communication bottleneck or a single point of failure. Conventional approaches may not be able to apply directly to such environments due to restricted queries and varied resource characteristics. Alternatively, a fully decentralized resource discovery service based on an unstructured overlay, which relies only on the information of resource attributes and characteristics, may be a feasible solution. One major challenge of such service is to locate desired and suitable resources without the global knowledge of distributed sharing resources. As a consequence, the more nodes the resource discovery service involves, the higher the network overhead incurs. In this paper, we proposed a direction-aware strategy which can alleviate the network traffic among unstructured information systems for distributed resource discovery service. Experimental results have demonstrated that the proposed approach achieves higher success rate at low cost and higher scalability.

Direction-aware resource discovery service in large-scale grid and cloud computing

With the consideration of scalability and robustness, distributed computing systems such as grids and clouds may exploit the P2P approach to enhance their performance. However, conventional techniques in P2P systems cannot be applied directly into grid systems due to restricted sort of queries for desired resources. In this paper, we consider a fully decentralized resource discovery service based on an unstructured overlay, where the major challenge is to locate desired resources without the global knowledge about sharing resource information. Consequently, more nodes involved in the resource discovery scheme may incur higher network overhead. To achieve an efficient resource discovery, this paper aims to alleviate the network traffic among unstructured information systems. Relying on the information of resource attributes and characteristics, we propose the direction-aware resource discovery scheme to improve the overall performance. Experimental results illustrate that the proposed approach is efficient and scalable compared with conventional approaches.

SARIDS: A Self-Adaptive Resource Index and Discovery System

Recently, the resource sharing systems apply the P2P technique to provide scalable multi-attribute range queries. However, due to the heterogeneity of resources and the variation of sharing policies in different providers, current P2P-based resource discovery systems may suffer the load imbalance problem in a large scale distributed system. In this paper, we propose a self-adaptive resource index and discovery system (SARIDS) to achieve load balancing. SARIDS adopts a two-tier architecture based on the structured P2P overlay. The intra-overlay is constructed by normal peers with the same attribute via the locality preserving hash function; and, the inter-overlay is constructed by super-peers with classified attributes in different intra-overlays. SARIDS supports not only the multi-attribute range queries but also the self-adaptive mechanisms for load balancing in the intra-overlay and among the intra-overlays. The simulation results show that SARIDS is scalable and efficient for load balancing even in the non-uniform peer range environment.

Efficient Network Structure of 5G Mobile Communications

5G mobile communications requires system and network considerations from many aspects. Instead of high spectral efficient physical layer communication, We introduce efficient network structure supplying a new design paradigm to meet user experience, spectral efficiency, and energy efficiency, under wide range of services and applications on top of 5G mobile communication networks, with virtual networking over software defined networking facilitating.

Community-Based M2M Framework Using Smart/HetNet Gateways for Internet of Things

In order to manage the Internet of things in a flexible and efficient way, this paper proposes a novel M2M framework using smart/HetNet gateways. Our approach is not only compatible to the M2M standard, but also enables the community-based coordination among gateways and devices. With smart and HetNet gateways, various types of requirements and applications can be fulfilled and handled at a local region. Accordingly, unnecessary network usage is avoided so as to reduce the traffic loads in mobile networks. We also implement a prototype to sustain an application scenario of IoT. In our prototype, the lamp is automatically switched on when a human face is detected. The demonstration shows that our system is practical and supports the subscription and notification in a community. Finally, experimental results reveal that some basic procedures can benefit from the shorter time and less uplink traffic if devices involved in an application are within the same region.

Cooperative Failure Detection in Multi-Overlay Environments

Multi-overlay environments have emerged due to the rapidly widespread of P2P applications. However, the synergy of multiple co-existing overlays still has not been fully exploited yet. Most of related research studies only focused on one of two issues that include the reduction of maintenance costs and the enhancement of system performance. On the other hand, failure detection is a necessary maintenance protocol for an overlay to ensure overlay resilience; however, independent failure detection in co-existing overlays introduces large probe messages as the number of those overlays increases. Therefore, this paper proposes a cooperative failure detection approach both to eliminate the redundant failure detection operations and to improve the failure detection mechanism in multi-overlay environments. Experimental results show that the proposed cooperative approach reduces more than 80% probe messages and shortens the detection time up to 60%.

G2G: A Meta-Grid Framework for the Convergence of P2P and Grids

Grid systems integrate distributed resources to form self-organization and self-management autonomies. Recently, for large-scale computation requirement, the collaboration of different grid systems is one of the hot research topics. In this paper, we propose a meta-grid framework, called G2G framework, to harmonize autonomic grids for realizing the federation of different grids. The G2G framework is a decentralized management framework on top of existing autonomic grid systems. It adopts a super-peer network to coordinate distributed grid systems. A super-peer overlay network is constructed for the communication among super-peers in different grid systems. The contribution of this study is to propose a G2G framework for the Grid-to-Grid federation and to implement a preliminary system. Experimental results show that the proposed meta-grid framework could improve the system performance in the G2G system.