University of Waterloo

About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.

Dynamically dimensioned search algorithm for computationally efficient watershed model calibration

Abstract: [1] A new global optimization algorithm, dynamically dimensioned search (DDS), is introduced for automatic calibration of watershed simulation models. DDS is designed for calibration problems with many parameters, requires no algorithm parameter tuning, and automatically scales the search to find good solutions within the maximum number of user-specified function (or model) evaluations. As a result, DDS is ideally suited for computationally expensive optimization problems such as distributed watershed model calibration. DDS performance is compared to the shuffled complex evolution (SCE) algorithm for multiple optimization test functions as well as real and synthetic SWAT2000 model automatic calibration formulations. Algorithms are compared for optimization problems ranging from 6 to 30 dimensions, and each problem is solved in 1000 to 10,000 total function evaluations per optimization trial. Results are presented so that future modelers can assess algorithm performance at a computational scale relevant to their modeling case study. In all four of the computationally expensive real SWAT2000 calibration formulations considered here (14, 14, 26, and 30 calibration parameters), results show DDS to be more efficient and effective than SCE. In two cases, DDS requires only 15–20% of the number of model evaluations used by SCE in order to find equally good values of the objective function. Overall, the results also show that DDS rapidly converges to good calibration solutions and easily avoids poor local optima. The simplicity of the DDS algorithm allows for easy recoding and subsequent adoption into any watershed modeling application framework.

An Efficient Identity-Based Batch Verification Scheme for Vehicular Sensor Networks

Abstract: With the adoption of state-of-the-art telecommunication technologies for sensing and collecting traffic related information, Vehicular Sensor Networks (VSNs) have emerged as a new application scenario that is envisioned to revolutionize the human driving experiences and traffic flow control systems. To avoid any possible malicious attack and resource abuse, employing a digital signature scheme is widely recognized as the most effective approach for VSNs to achieve authentication, integrity, and validity. However, when the number of signatures received by a Roadside Unit (RSU) becomes large, a scalability problem emerges immediately, where the RSU could be difficult to sequentially verify each received signature within 300 ms interval according to the current Dedicated Short Range Communications (DSRC) broadcast protocol. In this paper, we introduce an efficient batch signature verification scheme for communications between vehicles and RSUs (or termed vehicle- to-Infrastructure (V2I) communications), in which an RSU can verify multiple received signatures at the same time such that the total verification time can be dramatically reduced. We demonstrate that the proposed scheme can achieve conditional privacy preservation that is essential in VSNs, where each message launched by a vehicle is mapped to a distinct pseudo identity, while a trust authority can always retrieve the real identity of a vehicle from any pseudo identity. With the proposed scheme, since identity-based cryptography is employed in generating private keys for pseudo identities, certificates are not needed and thus transmission overhead can be significantly reduced.

Evolution in open source software: a case study

Abstract: Most studies of software evolution have been performed on systems developed within a single company using traditional management techniques. With the widespread availability of several large software systems that have been developed using an "open source" development approach, we now have a chance to examine these systems in detail, and see if their evolutionary narratives are significantly different from commercially developed systems. The paper summarizes our preliminary investigations into the evolution of the best known open source system: the Linux operating system kernel. Because Linux is large (over two million lines of code in the most recent version) and because its development model is not as tightly planned and managed as most industrial software processes, we had expected to find that Linux was growing more slowly as it got bigger and more complex. Instead, we have found that Linux has been growing at a super-linear rate for several years. The authors explore the evolution of the Linux kernel both at the system level and within the major subsystems, and they discuss why they think Linux continues to exhibit such strong growth.