Virtual numbers for virtual machines?

Knowing the number of virtual machines (VMs) that a cloud physical hardware can (further) support is critical as it has implications on provisioning and hardware procurement. However, current methods for estimating the maximum number of VMs possible on a given hardware is usually the ratio of the specifications of a VM to the underlying cloud hardware’s specifications. Such naive and linear estimation methods mostly yield impractical limits as to how many VMs the hardware can actually support. It was found that if we base on the naive division method, user experience on VMs at those limits would be severely degraded. In this paper, we demonstrate through experimental results, the significant gap between the limits derived using the estimation method mentioned above and the actual situation. We believe for a more practicable estimation of the limits of the underlying infrastructure

Propagation Models and Analysis for Mobile Phone Data Analytics

People in modern society use mobile phones as their primary way to retrieve information and to connect with others across the globe. The kinds of connections these devices support give rise to networks at many levels, from those among devices connected by near-field radio or bluetooth, to society-wide networks of phone calls made between individuals. This chapter introduces state-of-the-art propagation models that have been applied to understand such networks. It discusses how the models are used in many innovative studies, including how short-lived information spreads between phone callers, how malware spreads within public places, how to detect fraudulent and scamming activity on a phone network, and to predict the propensity of a user to unsubscribe from a mobile phone carrier. It concludes with a discussion of future research opportunities for the study of propagation modeling to mobile phone data analytics

The Importance of Outlier Relationships in Mobile Call Graphs

Mobile phones have become one of the primary tools for individuals to communicate, to access data networks, and to share information. Service providers collect data about the calls placed on their network, and these calls exhibit a large degree of variability. Providers model the structure of the relationships between network subscribers as a mobile call graph. In this paper, we apply a new measure to quantify by how much a relationship between users in a mobile call graph deviate from an average relationship. This measure is used to explore the connection between calling behaviors and the complex structure mobile call graphs take. We study a large call graph from a major service provider and learn that distant, outlier relationships play the largest role in maintaining connectivity between cellular users, and that calling features of users more strongly influence tie variation compared to social features. We also observe a rapid decay of its massively connected component as outlier ties are removed

Where do we Develop? Discovering Regions for Urban Investment in Senegal

The rate of urbanization in developing countries, defined as the speed with which a population shifts from rural to urban areas, is among the highest in the world. The disproportionate number of citizens that live in a small numbers of cities places incredible pressure on the largest cities in these countries, which may already be faced with limited resources, weak industrialization, and underdeveloped infrastructures. Urban planning researchers as well as policy makers have suggested that governments in developing countries make capital investments within and surrounding smaller cities to attract citizens away from large urban centers, thereby lowering the pressure placed on overpopulated urban centers and making it more attractive for citizens to migrate to the smaller cities. This paper proposes a methodology that maps signals in mobile phone usage data to longstanding urban planning theories. These signals are subsequently combined in an unsupervised learner to discover regions within which city investments should be made. Qualitative evaluations of the selected arrondissements illustrate the promise of our approach

The Importance of Outlier Relationships in Mobile Call Graphs

Mobile phones have become one of the primary tools for individuals to communicate, to access data networks, and to share information. Service providers collect data about the calls placed on their network, and these calls exhibit a large degree of variability. Providers model the structure of the relationships between network subscribers as a mobile call graph. In this paper, we apply a new measure to quantify by how much a relationship between users in a mobile call graph deviate from an average relationship. This measure is used to explore the connection between calling behaviors and the complex structure mobile call graphs take. We study a large call graph from a major service provider and learn that distant, outlier relationships play the largest role in maintaining connectivity between cellular users, and that calling features of users more strongly influence tie variation compared to social features. We also observe a rapid decay of its massively connected component as outlier ties are removed

Achieving dependability in software-defined networking - a perspective

In this paper we take a closer look at the operationof software defined networking (SDN) in intra-domain networks.The focus is on the dependability issues related to interworking ofSDN controllers, network OS (NOS), and forwarding in the dataplane. Both the separation of the control and data planes, and the(virtually) centralized control processes, are challenging from adependability perspective. In particular, consistency in operationand information is a challenge, both between the control and dataplanes, but also within a given plane. To ensure the necessarylevel of consistency there could be a conflict with the strict real-time requirements given by the per-flow operation of the SDNcontroller. A principle system model is introduced to discussthe consistency challenge, and to point out undesirable cyclicdependencies between functions that are necessary to configureand operate SDN. The separation of control processing andforwarding do also introduce structural vulnerabilities, whichare exemplified© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is the authors' accepted and refereed manuscript to the article