9335901
Performance upgrade for large object bases using disk arrays
The authors propose the use of multiple disks to increase the bandwidth of disk I/O so as to alleviate the I/O bottleneck problem existed in OODB applications. However, a major difficulty in using multiple disks for the support of OODBs is that an object may reference or be referenced by other objects through associations. This requires that the search of objects be sequential through the association links, which is sometimes referred to as the navigational search of objects in an object base. This restriction limits the concurrency in object retrieval and invalidates the use of multiple disks. Techniques such as clustering/indexing of objects do not help to resolve this problem. By using a two-phase query processing strategy previously proposed by them, objects of interest can be accessed in parallel from multiple disk. The aim of the paper is to design a probability-based evaluation model to estimate the performance of using multiple disks and to compare it with a single disk system. The result shows that the scheme is viable and a significant improvement is achieved while multiple disks are used.
20308502
Object signatures for supporting efficient navigation in object-oriented databases
Most methods that have been proposed to improve query processing in object-oriented databases are designed for the aggregation hierarchy. Although the structure of the generalization hierarchy is similar to the aggregation hierarchy, techniques developed for the aggregation hierarchy cannot fully use the characteristics of the generalization hierarchy to improve performance. We devise a new object signature for the generalization hierarchy. The object signature consists of two parts: a reference signature and a structure signature. The former can be used to eliminate objects that do not match the nested predicates specified in the query, and the latter can be used to eliminate objects that do not belong to the target classes. We propose some processing methods using the object signatures for queries that involve generalization hierarchies. In addition, we define cost models of the object signature and then compare the performance of the traditional query processing method with the object signature method. The results show that using the object signatures can effectively reduce the number of disk accesses in a query.
18796888
Design and Performance Evaluation of Broadcast Algorithms for Time-Constrained Data Retrieval
We refer "time-constrained services" to those requests that have to be replied to within a certain client-expected time duration. If the answer cannot reach the client within this expected time, the value of the information may seriously degrade or even become useless. On-demand channels may not be able to handle all time-constrained services without degrading the performance. How to handle these services in broadcast channels becomes crucial to balance the load of wireless systems. In this paper, we study this problem and find the minimum number of broadcast channels required for such a task. Also, we propose solutions for this problem when the available channels are insufficient. Our performance result reveals that only a moderate number of channels is required to promote these time-constrained services
2051959
Performance Evaluation of Forwarding Strategies for Location Management in Mobile Networks
This paper presents a methodology for evaluating the performance of forwarding strategies for location management in a personal communication services (PCS) mobile network. A forwarding strategy in the PCS network can be implemented by two mechanisms: a forwarding operation which follows a chain of databases to locate a mobile user and a resetting operation which updates the databases in the chain so that the current location of a mobile user can be known directly without having to follow a chain of databases. In this paper, we consider the PCS network as a server whose function is to provide services to the mobile user for ‘updating the location of the user as the user moves across a database boundary’ and ‘locating the mobile user’. We use a Markov chain to describe the behavior of the mobile user and analyze the best time when forwarding and resetting should be performed in order to optimize the service rate of the PCS network. We demonstrate the applicability of our approach with hexagonal and mesh coverage models for the PCS network and provide a physical interpretation of the result.
34408109
Modeling GIS Data Using OMEGA
31930663
Minimization of resource consumption for multidatabase query optimization
Due to the autonomy of individual databases, a multidatabase system (MDBS) has no control over the task execution within each database system. This complicates the issue of query optimization in a MDBS. Past researchers tackled this problem mainly by regenerating the cost model of each participating database systems. However a completely autonomous participating database system does nor own the information (data) as well as the mechanism (software) for converting data of one database to another to resolve the data type conflict problems that can occur in any MDBS environment. In addition, unpredictable factors that can drastically deviate the accuracy of a regenerated cost model (in the past research) come into play at unknown time. This confines the processing of an intersite operation (such as a join over two relations of different databases) to the MDBS only. The participating database systems will not be able to share the workload of the MDBS under this circumstance. Hence, minimizing the consumption of system resources of the MDBS is an urgent problem. The authors propose three scheduling algorithms that are used in the MDBS to reduce the processing cost of a multidatabase query. A major difference between the strategies and the past methods is that ours do not require the knowledge of the cost models of the participating databases.
6076905
Finite-horizon scheduling of radar dwells with online template construction
Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon.
5320438
On quality of service optimization with discrete QoS options
We present a QoS management framework that enables us to quantitatively measure QoS, and to analytically plan and allocate resources. In this model, end users' quality preferences are considered when system resources are apportional across multiple applications such that the net utility that accrues to the end-users is maximized. We previously worked with continuous QoS dimensions, and assumed that the utility gained by improvements along a QoS dimension were always representable by concave functions. In this paper we relax both assumptions. One, we support discrete QoS operating points. Two, we make no assumptions about the concavity of the utility functions. Using these as the basis, we tackle the problem of maximizing system utility by allocating a single finite resource to satisfy the QoS requirements of multiple applications along multiple QoS dimensions. We present two near-optimal algorithms to solve this problem. The first yields an allocation within a known bounded distance from the optimal solution, and the second yields an allocation whose distance from the optimal solution can be explicitly controlled by the QoS manager, We compare the run-times of these near-optimal algorithms and their solution quality relative to the optimal allocation, which in turn is computed using dynamic programming. These detailed evaluations provide practical insight into which of these algorithms can be used online in real-time systems.
16111193
Bounding Cache-Related Preemption Delay for Real-Time Systems
Cache memory is used in almost all computer systems today to bridge the ever increasing speed gap between the processor and main memory. However, its use in multitasking computer systems introduces additional preemption delay due to the reloading of memory blocks that are replaced during preemption. This cache-related preemption delay poses a serious problem in realtime computing systems where predictability is of utmost importance. We propose an enhanced technique for analyzing and thus bounding the cache-related preemption delay in fixed-priority preemptive scheduling focusing on instruction caching. The proposed technique improves upon previous techniques in two important ways. First, the technique takes into account the relationship between a preempted task and the set of tasks that execute during the preemption when calculating the cache-related preemption delay. Second, the technique considers the phasing of tasks to eliminate many infeasible task interactions. These two features are expressed as constraints of a linear programming problem whose solution gives a guaranteed upper bound on the cache-related preemption delay. This paper also compares the proposed technique with previous techniques using randomly generated task sets. The results show that the improvement on the worst-case response time prediction by the proposed technique over previous techniques ranges between 5 percent and 18 percent depending on the cache refill time when the task set utilization is 0.6. The results also show that as the cache refill time increases, the improvement increases, which indicates that accurate prediction of cache-related preemption delay by the proposed technique becomes increasingly important if the current trend of widening speed gap between the processor and main memory continues.
7151560
A source identification scheme against DDoS attacks in cluster interconnects
Designing secure clusters has recently become a critical issue to make these systems robust to attacks from the Internet. The Distributed Denial of Service (DDoS) attack is one of the most serious problems in the current Internet. To defend against DDoS attacks, clusters usually depend on firewalls or Intrusion Detection Systems (IDS). However, once firewall and IDS are breached, the impact of DDoS attack within a cluster can be severe. That is because one infected system or one malicious user, which is believed to be trustworthy, may instantly paralyze the whole cluster through the high speed network. In this paper, we present a deterministic distance packet marking (DDPM) scheme to identify the source nodes generating spoofed IP packets in cluster interconnects. The scheme can be applied to many cluster interconnects such as mesh, torus and hypercube, which are popular in many commercial systems. Our scheme is practically attractive since it is scalable to large networks and does not incur much processing overhead on both switches and nodes.
11513651
A scalable solution to the multi-resource QoS problem
The problem of maximizing system utility by allocating a single finite resource to satisfy discrete Quality of Service (QoS) requirements of multiple applications along multiple QoS dimensions was studied previously. In this paper we consider the more complex problem of apportioning multiple finite resources to satisfy the QoS needs of multiple applications along multiple QoS dimensions. In other words, each application, such as video-conferencing, needs multiple resources to satisfy its QoS requirements. We evaluate and compare three strategies to solve this provably NP-hard problem. We show that dynamic programming and mixed integer programming compute optimal solutions to this problem but exhibit very long running times. We then adapt the mixed integer programming problem to yield near-optimal results with smaller running times. Finally, we present an approximation algorithm based on a local search technique that is less than 5% away from the optimal solution but which is more than two orders of magnitude faster. Perhaps more significantly, the local search technique turns out to be very scalable and robust as the number of resources required by each application increases.