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We evolve a methodology and define a metric to evaluate Tactile Internet based Cyber-Physical Systems or Tactile Cyber-Physical Systems (TCPS). Towards this goal, we adopt the step response analysis, a well-known control-theoretic method. The adoption includes replacing the human operator (or master) with a controller with known characteristics and analyzing its response to slave side step disturbances. The resulting step response curves demonstrate that the \textit{Quality of Control} (QoC) metric is sensitive to control loop instabilities and serves as a good indicator of cybersickness experienced by human operators. We demonstrate the efficacy of the proposed methodology and metric through experiments on a TCPS testbed. The experiments include assessing the suitability of several access technologies, intercontinental links, network topologies, network traffic conditions and testbed configurations. Further, we validate our claim of using QoC to predict and quantify cybersickness through experiments on a teleoperation setup built using Mininet and VREP.

We present our ``Zero Energy Network'' (ZEN) protocol stack for energy harvesting wireless sensor networks applications. The novelty in our work is $4$ fold: (1) Energy harvesting aware fully featured MAC layer. Carrier sensing, Backoff algorithms, ARQ, RTS/CTS mechanisms, Adaptive Duty Cycling are either auto configurable or available as tunable parameters to match the available energy (b) Energy harvesting aware Routing Protocol. The multi-hop network establishes routes to the base station using a modified version of AODVjr routing protocol assisted by energy predictions. (c) Application of a time series called ``Holt-Winters'' for predicting the incoming energy. (d) A distributed smart application running over the ZEN stack which utilizes a multi parameter optimized perturbation technique to optimally use the available energy. The application is capable of programming the ZEN stack in an energy efficient manner. The energy harvested distributed smart application runs on a realistic solar energy trace with a three year seasonality database. We implement a smart application, capable of modifying itself to suit its own as well as the network's energy level. Our analytical results show a close match with the measurements conducted over EHWSN testbed., Comment: 12 pages, 2013

A simplified description of Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) is presented. We have adapted the TOPSIS description from existing Fuzzy theory literature and distilled the bare minimum concepts required for understanding and applying TOPSIS. An example has been worked out to illustrate the application of TOPSIS for a multi-criteria group decision making scenario., Comment: 3 pages