Urban stormwater runoff has been a critical and chronic problem in the quantity and quality of receiving waters,
resulting in a major environmental concern. To address this problem engineers and professionals have developed a
number of solutions which include various monitoring and modeling techniques. The most fundamental issue in these
solutions is accurate monitoring of the quantity and quality of the runoff from both combined and separated sewer
systems. This study proposes a new water quantity monitoring system, based on recent developments in sensor
technology. Rather than using a single independent sensor, we harness an intelligent sensor platform that integrates
various sensors, a wireless communication module, data storage, a battery, and processing power such that more
comprehensive, efficient, and scalable data acquisition becomes possible. Our experimental results show the feasibility
and applicability of such a sensor platform in the laboratory test setting.
Due to skewed popularity of objects in many continuous media
applications, data placement techniques such as selective
replication have been introduced to resolve potential load
imbalance problem by providing more replicas for more popular
objects, resulting in a higher availability of hot objects and a
more efficient usage of bounded storage space. To fully harness
the advantage of selective replication technique, one may need to
periodically reconfigure the number of instances of objects and
data placement of them to tune up the system performance because,
in reality, access frequency varies over time in many reasons.
Reconfiguration usually requires time and disk bandwidth resulting
in a degradation of the system performance during the process.
This paper proposes algorithms for dynamic reconfiguration of
continuous media servers based on ever changing popularity of
objects. This paper quantifies the expected startup latency and
reconfiguration overhead. Proposed analytic models and simulation
results demonstrate that the proposed reconfiguration process is
feasible in a reasonable amount of time. They also show tolerable
performance degradation due to bandwidth overhead during
reconfiguration process, which is critical for most real
Due to increased interests in interactive personalized multimedia services, the design of continuous media (CM) severs in support of this functionality has received attention from industry and academia. These systems automatically create a sequence of CM segments optimized to the interests of each user based on their predefined preferences and impromptu queries. Applications such as distance learning, news-on-demand, interactive training, and home shopping would be significantly improved with this functionality. Two critical issues are 1) automatic creation of an optimized script for each user, and 2) data management and retrieval to maximize the performance of servers in a multi-user environment. Due to the maximized flexibility of presentation and potential conflicts among requirements from concurrent users while sharing huge amount of CM data without redundancy, the design of a CM sever that supports these applications, especially data placement and retrieval scheduling, is challenging. This paper investigates and proposes data placement and retrieval scheduling techniques on multi-disk CM servers to support such applications. These include how to share the same content among multiple users, how to compose a personalized content on demand for each user and support continuous display of the edited content without any jitters or interruptions, termed hiccups. The proposed techniques solve the problems by providing a fast retrieval of CM data using random data placement across disks with deadline-driven scheduling and prefetching them with a minimal latency to statistically guarantee a continuous display. Simulation results demonstrate the feasibility of on-demand composition and continuous display of personalized content with a hiccup probability less than a millionth. They also show less than a second startup latency, which is acceptable for most interactive applications.
In a scalable server that supports the retrieval and display of continuous media, both the number of simultaneous displays and the expected startup latency of a display increases as a function of additional disk bandwidth. Based on a striping technique and around-robin placement of data, this paper describes object replication and request migration as two alternative techniques to minimize startup latency. In addition to developing analytical models for these two techniques, we report on their implementation using a scalable server. The results obtained from both the analytical models and the experimental system demonstrate the effectiveness of the proposed techniques.
A challenging task when designing a video server is to support the performance criteria of its target application, i.e., both its desired number of simultaneous displays and the waiting tolerance of a display. With a multi-disk video server, the placement of data has a significant impact on the overall performance of a system. This study quantifies the tradeoffs associated with alternative organization of data across multiple disks. We describe a planner that configures a system to: (1) support the performance criteria of an application, and (2) minimize the cost of a system. The experimental results demonstrate the superiority and flexibility of using the planner to configure a system.
Conference Committee Involvement (3)
Multimedia Computing and Networking 2009
19 January 2009 | San Jose, California, United States
Multimedia Computing and Networking 2008
30 January 2008 | San Jose, California, United States