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Although nanoscale sensors provide valuable data at finer levels, their size limitations impose difficulties in designing nanoscale systems. The limitations in the hardware part of such systems consequentially affect the software part too. Routing, being one of the main functions of the communication software of nano-sensors, it requires customised design, where constraints such as the energy efficiency have to be considered. Knowing that communication is the most energy consuming operation for the sensor networks, in general, the importance of routing protocol becomes clear. With this motivation, the existing routing protocols for the wireless nano-sensor networks are reviewed. The presentation of the classification and comparison of the existing protocols, followed by the discussion on the proposed simple energy-aware routing protocol based on the 'backward-learning' paradigm. Simulations are carried out in ns-3 by using Nano-Sim package. Results are listed to show the efficiency of the proposed method in terms of energy use and the packet statistics.

Fractal measures like fractal dimension (FD), lacunarity, succolarity measure the geometrical complexity of objects and could be used to describe texture information of the images. For this purpose different box counting algorithms were developed to estimate FD. However the existing box-counting methods usually suffer from under counting or over counting, introducing difficulties in obtaining the exact value of the FD. This paper focuses on the box-counting's power in uniquely identifying patterns and presents a new approach which considers the aggregate effects of all the gray levels in the boxes, rather than considering only two gray levels, (min and max) as in the case of traditional differential box-counting method. The proposed method uses new counting measure based on volume percentage of the gray levels inside the boxes. Results from experiments tabulated to depict the improved effect of the proposed method in recognition of the noisy test images from Brodatz Texture and normal test images from CASIA-V3 Iris Databases.

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Though there have been several recent e orts to develop disk based video servers, these approaches have all ignored the topic of updates and disk server crashes. In this paper, we present a priority based model for building video servers that handle two classes of events: user events that could include enter, play, pause, rewind, fast-forward, exit, as well as system events such as insert, delete, server-down, server-up that correspond to uploading new movie blocks onto the disk(s), eliminating existing blocks from the disk(s), and/or experiencing a disk server crash. We will present algorithms to handle such events. Our algorithms are provably correct, and computable in polynomial time. Furthermore, we guarantee that under certain reasonable conditions, continuing clients experience jitter free presentations. We further justify the e ciency of our techniques with a prototype implementation and experimental results.