No description available.

Stretchable Electronics is an emerging class of electronics that allow electronics to be bent, conform, ex and stretch while still retaining its full functionality. Other than bending, existing and conforming, adding stretchability to electronic systems can open up a new frontier for a myriad of applications. Especially in the medical sector, these stretchable devices can increase the scope of monitoring and ease and comfort of the patient. All kinds of wearable devices can be based on these technologies to augment our daily lives. With the kind of state of art technology available to the common man today, the bar has already been set for the performance of such devices. Hence, its imperative that these stretchable devices perform at this level and should be capable of adapting to the market to serve the mass requirement. Hence, it becomes inevitable to use metal interconnects to provide very low resistance and easy adhesion to commercial electronic components. Another aspect of such devices is an adhesion ability with which we can attach it to various kinds of surfaces. In this thesis, we propose a new multi-layered PDMS structure approach to bring stretchability in the device. For all kinds of adhesion requirements, various ratios of PDMS: Cross-linker have been used. These different ratios of PDMS: Cross-linker changes the mechanical and adhesive properties of the cured PDMS. Hence, the same material can be used as the stretchable substrate as well as to serve various adhesion requirements. A soft adhesion allows us to attach it to the human body/other surfaces. The adhesion can be tailored to be quite conformal and strong, yet its removal is quite gentle to the skin. A higher curing ratio makes the PDMS very sticky and soft. Aluminum/Copper foils can be directly stuck upon it and tracks can be then etched out to get a printed circuit. Since this adhesive layer is quite soft, it acts as a cushion and reduces the amount of stress transferred to the metal interconnects. Hence, stretchable circuits with metal interconnects can be realized. The electronic components can be then attached upon it via normal soldering techniques/using conductive ink. Various devices that can be built with the proposed techniques have been coined the term CAS (Conformal Active Sheets) to allow easy reference to such kind of devices. Since the substrate is soft, physical handling of such devices becomes an issue as one tries to transfer the circuit pattern. Hence, direct etching of the metal foil was explored via high pulsed current discharge technique. A CNC machine was also designed to try various ways of direct etching of the metal foil in an accurate and repeatable fashion.

Most of the cellular tra c (voice and data) is generated indoors. Due to attenuation from walls, quality of service (QoS) of di erent applications degrades for indoor tra c. Thus in order to provide QoS for such users the Macro base station (MBS) has to transmit at high power. This increases recurring costs to the service provider and contributes to green house emissions. Hence, Femtocells (FC) are considered as an option. Femto Access Points (FAP) are low cost, low powered, small base stations deployed indoors by customers. A substantial part of indoor tra c is diverted from the Macrocell (MC) through the FAP. Since the FCs also use the same channels as the MC, deployment of FCs causes interference to not only its neighbouring FCs but also to the users in the MC. Thus, we need better interference management techniques for this system. In this thesis, we consider a system with multiple Femtocells operating in a Macrocell. FCs and MC use same set of multiple channels and support multiple users. Each user may have a minimum rate requirement. To limit interference to the MC, there is a peak power constraint on each channel. In the rst part of the thesis, we consider sparsely deployed FCs where the interference between the FCs is negligible. For this we formulate the problem of channel allocation and power control in each FC. We develop computationally e cient, suboptimal algorithms to satisfy QoS of each user in the FC. If QoS of each user is not satis ed, we provide solutions which are fair to all the users. In the second part of the thesis, we consider the case of densely deployed FCs where we formulate the problem of channel allocation and power control in each Femtocell as a noncooperative Game. We develop e cient decentralized algorithms to obtain a Nash equilibrium (NE) at which QoS of each user is satis ed. We also obtain e cient decentralized algorithms to obtain fair NE when it may not be feasible to satisfy the QoS of all the users in the FC. Finally, we extend our algorithms to the case where there may be voice and data users in the system. In the third part of the thesis, we continue to study the problem setup in the second part, where we develop algorithms which can simultaneously consider the cases where QoS of users can be satis ed or not. We provide algorithms to compute Coarse Correlated Equilibrium (CCE), Pareto optimal points and Nash bargaining solutions. In the nal part of the thesis, we consider interference limit at the MBS and model FCs as sel sh nodes. The MBS protects itself via pricing subchannels per usage. We obtain a Stackelberg equilibrium (SE) by considering MBS as a leader and FCs as followers.

With online social networks such as Facebook and Twitter becoming globally popular, there is renewed interest in understanding the structural and dynamical properties of social networks. In this thesis we study several stochastic models arising in the context of the spread of influence or information in social networks. Our objective is to provide compact and accurate quantitative descriptions of the spread processes, to understand the effects of various system parameters, and to design policies for the control of such diffusions. One of the well established models for influence spread in social networks is the threshold model. An individual’s threshold indicates the minimum level of “influence” that must be exerted, by other members of the population engaged in some activity, before the individual will join the activity. We begin with the well-known Linear Threshold (LT) model introduced by Kempe et al. [1]. We analytically characterize the expected influence for a given initial set under the LT model, and provide an equivalent interpretation in terms of acyclic path probabilities in a Markov chain. We derive explicit optimal initial sets for some simple networks and also study the effectiveness of the Pagerank [2] algorithm for the problem of influence maximization. Using insights from our analytical characterization, we then propose a computationally efficient G1-sieving algorithm for influence maximization and show that it performs on par with the greedy algorithm, through experiments on a coauthorship dataset. The Markov chain characterisation gives only limited insights into the dynamics of influence spread and the effects of the various parameters. We next provide such insights in a restricted setting, namely that of a homogeneous version of the LT model but with a general threshold distribution, by taking the fluid limit of a probabilistically scaled version of the spread Markov process. We observe that the threshold distribution features in the fluid limit via its hazard function. We study the effect of various threshold distributions and show that the influence evolution can exhibit qualitatively different behaviors, depending on the threshold distribution, even in a homogeneous setting. We show that under the exponential threshold distribution, the LT model becomes equivalent to the SIR (Susceptible-Infected-Recovered) epidemic model [3]. We also show how our approach is easily amenable to networks with heterogeneous community structures. Hundreds of millions of people today interact with social networks via their mobile devices. If the peer-to-peer radios on such devices are used, then influence spread and information spread can take place opportunistically when pairs of such devices come in proximity. In this context, we develop a framework for content delivery in mobile opportunistic networks with joint evolution of content popularity and availability. We model the evolution of influence and content spread using a multi-layer controlled epidemic model, and, using the monotonicity properties of the o.d.e.s, prove that a time-threshold policy for copying to relay nodes is delay-cost optimal. Information spread occurs seldom in isolation on online social networks. Several contents might spread simultaneously, competing for the common resource of user attention. Hence, we turn our attention to the study of competition between content creators for a common population, across multiple social networks, as a non-cooperative game. We characterize the best response function, and observe that it has a threshold structure. We obtain the Nash equilibria and study the effect of cost parameters on the equilibrium budget allocation by the content creators. Another key aspect to capturing competition between contents, is to understand how a single end-user receives and processes content. Most social networks’ interface involves a timeline, a reverse chronological list of contents displayed to the user, similar to an email inbox. We study competition between content creators for visibility on a social network user’s timeline. We study a non-cooperative game among content creators over timelines of fixed size, show that the equilibrium rate of operation under a symmetric setting, exhibits a non-monotonic behavior with increasing number of players. We then consider timelines of infinite size, along with a behavioral model for user’s scanning behavior, while also accounting for variability in quality (influence weight) among content creators. We obtain integral equations, that capture the evolution of average influence of competing contents on a social network user’s timeline, and study various content competition formulations involving quality and quantity.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.