8855758
New Disk Scheduling Algorithms for Reduced Rotational Latency
Disk arm scheduling algorithms have been studied for many years to increase disk I/O performance. Most of the disks by the early 1980’s are characterized as a linear seek time and their seek time is responsible for the most time of disk access. So, the existing disk scheduling algorithms have focused on the reduction of the average seek distance. Seek time has improved greatly and today’s disks usually have nonlinear seek time characteristics, whereas the rotation speed has been steady at the 3600 RPM. So, it is of value to reduce average rotational latency. In this paper we propose two disk scheduling algorithms, i.e. Shortest Rotational Latency First(SRLF) and Shortest Access Tie Fist(SATF) for reduced rotational latency. SRLF services first a request with the shortest expected rotational latency and SATF services first a request with the shortest expected access time. We analyze the expected access time of the request serviced first by each of SSTF and SRLF under the uniform cylinder access. We evaluated the response time of SSTF, SRLF, and SATF through the simulations under the uniform and localized cylinder access. The results of the analysis and simulations show that the algorithms proposed in this paper are more efficient than SSTF which is known for the fastest response time.
6919897
An Accurate Worst Case Timing Analysis for RISC Processors
An accurate and safe estimation of a task's worst case execution time (WCET) is crucial for reasoning about the timing properties of real-time systems. In RISC processors, the execution time of a program construct (e.g., a statement) is affected by various factors such as cache hits/misses and pipeline hazards, and these factors impose serious problems in analyzing the WCETs of tasks. To analyze the timing effects of RISC's pipelined execution and cache memory, we propose extensions to the original timing schema where the timing information associated with each program construct is a simple time-bound. In our approach, associated with each program construct is worst case timing abstraction, (WCTA), which contains detailed timing information of every execution path that might be the worst case execution path of the program construct. This extension leads to a revised timing schema that is similar to the original timing schema except that concatenation and pruning operations on WCTAs are newly defined to replace the add and max operations on time-bounds in the original timing schema. Our revised timing schema accurately accounts for the timing effects of pipelined execution and cache memory not only within but also across program constructs. This paper also reports on preliminary results of WCET analysis for a RISC processor. Our results show that tight WCET bounds (within a maximum of about 30% overestimation) can be obtained by using the revised timing schema approach.
2296282
On the error probability of binary and M-ary signals in Nakagami-m fading channels
In this letter, we present new closed-form formulas for the exact average symbol-error rate (SER) of binary and M-ary signals over Nakagami-m fading channels with arbitrary fading index m. Using the well-known moment generating function-based analysis approach, we express the average SER in terms of the higher transcendental functions such as the Gauss hypergeometric function, Appell hypergeometric function, or Lauricella function. The results are generally applicable to arbitrary real-valued m. Furthermore, with the aid of reduction formulas of hypergeometric functions, we show previously published results for Rayleigh fading (m=1) as special cases of our expressions.
7642189
Capacity of multiple-antenna fading channels: spatial fading correlation, double scattering, and keyhole
The capacity of multiple-input multiple-output (MIMO) wireless channels is limited by both the spatial fading correlation and rank deficiency of the channel. While spatial fading correlation reduces the diversity gains, rank deficiency due to double scattering or keyhole effects decreases the spatial multiplexing gains of multiple-antenna channels. In this paper, taking into account realistic propagation environments in the presence of spatial fading correlation, double scattering, and keyhole effects, we analyze the ergodic (or mean) MIMO capacity for an arbitrary finite number of transmit and receive antennas. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is allocated to each of the transmit antennas. Using some statistical properties of complex random matrices such as Gaussian matrices, Wishart (1928) matrices, and quadratic forms in the Gaussian matrix, we present a closed-form expression for the ergodic capacity of independent Rayleigh-fading MIMO channels and a tight upper bound for spatially correlated/double scattering MIMO channels. We also derive a closed-form capacity formula for keyhole MIMO channels. This analytic formula explicitly shows that the use of multiple antennas in keyhole channels only offers the diversity advantage, but provides no spatial multiplexing gains. Numerical results demonstrate the accuracy of our analytical expressions and the tightness of upper bounds.
14141426
Efficient Enforcement of Security Policies Based on Tracking of Mobile Users
Recent advances to mobile communication, Global Positioning System (GPS) and Radio Frequency Identification (RFID) technologies have propelled the growth of a number of mobile services. These require maintaining mobile object's location information and efficiently serving access requests on the past, present and future status of the moving objects. Moreover, these services raise a number of security and privacy challenges. To address this, security policies are specified to ensure controlled access to the mobile user's location and movement trajectories, their profile information, and stationary resources based on the mobile user's spatiotemporal information. Considering the basic authorization specification 〈subject, object, privilege 〉, in a mobile environment, a moving object can be a subject, an object, or both. Serving an access request requires to search for the desired moving objects that satisfy the query, as well as enforce the security policies. 
 
Often, enforcing security incurs overhead, and as a result may degrade the performance of a system. To alleviate this problem, recently Atluri and Guo have proposed an unified index structure, STPR-tree, to organize both the moving objects and authorizations specified over them. However, the STPR-tree is not capable supporting security policies based on tracking of mobile users. In this paper, we present an index structure, called SPPF-tree, which maintains past, present and future positions of the moving objects along with authorizations by employing partial persistent storage. We demonstrate how the SPPF-tree can be constructed and maintained, and provide algorithms to process two types of access requests, including moving object requests by stationary subjects such as locate and track, and stationary object requests by moving subjects.
9432088
Response modeling with support vector machines
Support Vector Machine (SVM) employs Structural Risk Minimization (SRM) principle to generalize better than conventional machine learning methods employing the traditional Empirical Risk Minimization (ERM) principle. When applying SVM to response modeling in direct marketing, however, one has to deal with the practical difficulties: large training data, class imbalance and scoring from binary SVM output. For the first difficulty, we propose a way to alleviate or solve it through a novel informative sampling. For the latter two difficulties, we provide guidelines within SVM framework so that one can readily use the paper as a quick reference for SVM response modeling: use of different costs for different classes and use of distance to decision boundary, respectively. This paper also provides various evaluation measures for response models in terms of accuracies, lift chart analysis, and computational efficiency.
1668855
Fast Pattern Selection Algorithm for Support Vector Classifiers: Time Complexity Analysis
Training SVM requires large memory and long cpu time when the pattern set is large. To alleviate the computational burden in SVM training, we propose a fast preprocessing algorithm which selects only the patterns near the decision boundary. The time complexity of the proposed algorithm is much smaller than that of the naive M 2 algorithm