Load Balancing in the Non-Degenerate Slowdown Regime

We analyse Join-the-Shortest-Queue in a contemporary scaling regime known as the Non-Degenerate Slowdown regime. Join-the-Shortest-Queue (JSQ) is a classical load balancing policy for queueing systems with multiple parallel servers. Parallel server queueing systems are regularly analysed and dimensioned by diffusion approximations achieved in the Halfin-Whitt scaling regime. However, when jobs must be dispatched to a server upon arrival, we advocate the Non-Degenerate Slowdown regime (NDS) to compare different load-balancing rules. In this paper we identify novel diffusion approximation and timescale separation that provides insights into the performance of JSQ. We calculate the price of irrevocably dispatching jobs to servers and prove this to within 15% (in the NDS regime) of the rules that may manoeuvre jobs between servers. We also compare ours results for the JSQ policy with the NDS approximations of many modern load balancing policies such as Idle-Queue-First and Power-of-$d$-choices policies which act as low information proxies for the JSQ policy. Our analysis leads us to construct new rules that have identical performance to JSQ but require less communication overhead than power-of-2-choices.Comment: Revised journal submission versio

Performance analysis of server selection schemes for Video on Demand servers

Web Services have gained considerable attention over the last few years. This is due to increase in use of the Internet which results in increased web traffic. Web servers find applications in E-commerce and Video-on-Demand(VoD) systems which have resulted in speedy growth of the web traffic. Therefore the concept of load balancer aimed to distribute the tasks to different Web Servers to reduce response times was introduced. Each request was assigned a Web Server decided by the load balancer in such a way that tasks were uniformly distributed among the available servers. Server selection algorithms are aimed to meet the QoS for interactive VoD.This thesis attempts to analyze the performance of FCFS, Randomized, Genetic algorithms and Heuristics algorithms for selecting server to meet the VoD requirement . Performance of these algorithms have been simulated with parameters like makespan and average resource utilization for different server models. This thesis presents an efficient heuristic called Ga-max-min for distributing the load among different servers. Heuristics like min-min and max-min are also applied to heterogeneous server farms and the result is compared with the proposed heuristic for VoD Servers. Ga-max-min was found to provide lower makespan and higher resource utilization than the genetic algorithm.Extensive simulations have been carried out by the simulator designed using MATLAB R2010a

The Graph Curvature Calculator and the curvatures of cubic graphs

We classify all cubic graphs with either non-negative Ollivier-Ricci curvature or non-negative Bakry-\'Emery curvature everywhere. We show in both curvature notions that the non-negatively curved graphs are the prism graphs and the M\"obius ladders. We also highlight an online tool for calculating the curvature of graphs under several variants of these curvature notions that we use in the classification. As a consequence of the classification result we show, that non-negatively curved cubic expanders do not exist

Secure Digital Information Forward Using Highly Developed AES Techniques in Cloud Computing

Nowadays, in communications, the main criteria are ensuring the digital information and communication in the network. The normal two users' communication exchanges confidential data and files via the web. Secure data communication is the most crucial problem for message transmission networks. To resolve this problem, cryptography uses mathematical encryption and decryption data on adaptation by converting data from a key into an unreadable format. Cryptography provides a method for performing the transmission of confidential or secure communication. The proposed AES (Advanced Encryption Standard)-based Padding Key Encryption (PKE) algorithm encrypts the Data; it generates the secret key in an unreadable format. The receiver decrypts the data using the private key in a readable format. In the proposed PKE algorithm, the sender sends data into plain Text to cypher-text using a secret key to the authorized person; the unauthorized person cannot access the data through the Internet; only an authorized person can view the data through the private key. A method for identifying user groups was developed. Support vector machines (SVM) were used in user behaviour analysis to estimate probability densities so that each user could be predicted to launch applications and sessions independently. The results of the proposed simulation offer a high level of security for transmitting sensitive data or files to recipients compared to other previous methods and user behaviour analysis

Building Confidential and Efficient Query Services in the Cloud with RASP Data Perturbation

With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the RASP data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional ranges, which allows existing indexing techniques to be applied to speedup range query processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to process the kNN queries. We have carefully analyzed the attacks on data and queries under a precisely defined threat model and realistic security assumptions. Extensive experiments have been conducted to show the advantages of this approach on efficiency and security.Comment: 18 pages, to appear in IEEE TKDE, accepted in December 201

Enhancing System Transparency, Trust, and Privacy with Internet Measurement

While on the Internet, users participate in many systems designed to protect their information’s security. Protection of the user’s information can depend on several technical properties, including transparency, trust, and privacy. Preserving these properties is challenging due to the scale and distributed nature of the Internet; no single actor has control over these features. Instead, the systems are designed to provide them, even in the face of attackers. However, it is possible to utilize Internet measurement to better defend transparency, trust, and privacy. Internet measurement allows observation of many behaviors of distributed, Internet-connected systems. These new observations can be used to better defend the system they measure. In this dissertation, I explore four contexts in which Internet measurement can be used to the aid of end-users in Internet-centric, adversarial settings. First, I improve transparency into Internet censorship practices by developing new Internet measurement techniques. Then, I use Internet measurement to enable the deployment of end-to-middle censorship circumvention techniques to a half-million users. Next, I evaluate transparency and improve trust in the Web public-key infrastructure by combining Internet measurement techniques and using them to augment core components of the Web public-key infrastructure. Finally, I evaluate browser extensions that provide privacy to users on the web, providing insight for designers and simple recommendations for end-users. By focusing on end-user concerns in widely deployed systems critical to end-user security and privacy, Internet measurement enables improvements to transparency, trust, and privacy.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163199/1/benvds_1.pd