We exploit spatiotemporal correlation in sensor data and redundant binary number system based representation for encoding data, where the number of 0 s in the encoded data is significantly larger than the other symbols. Next, using a hybrid FSK-ASK modulation/demodulation technique with a non-coherent receiver, we have designed an energy-efficient communication scheme where the transmitter is kept silent during the transmission of the dominant symbol in the encoded messages. In contrast to the conventional techniques of data reduction and aggregation which exploit temporal and spatial correlation, our technique does not require dropping any data value while generating significantly more transmission energy savings. Our approach is particularly useful for sustainable energy-efficient communications in IoT applications like environment monitoring, agriculture, etc., where dropping any data value may not be desirable. Simulation results on different real-life sensor data sets using several popular low-cost, low data-rate transceivers like the RFM TR 1,000 show about$90.06\% - 90.86\%$savings in transmitter energy expenditure over conventional BFSK, and$15\% - 20\%$savings at receiver. Simulation results also demonstrate a proportionately reduced$CO_{2}$footprint generation of$0.12 - 0.14$mg/day only, when using the RFM TR 1,000 radio. These savings are considerably higher than those generated with the existing techniques.

In a natural disaster, when there is a sudden rush in vehicle movement from dense residential areas of a city towards some designated evacuation centers, traffic needs to be distributed along the road network in an optimal way so as to minimize the travel time for reaching those evacuation centers. We address this traffic distribution problem in a$k \times k$Manhattan road network with multiple traffic generating sources and a single fixed destination (sink) at a corner point. We first consider queuing delay at each grid point along with a fixed link delay. We then extend our idea to consider a rectangular grid and also real-life road networks where some of the links may be absent. We present a traffic distribution algorithm that would minimize the average time of all vehicles to reach the given destination point. Simulation of our algorithm using SUMO on the grid-structured road map of Manhattan borough in New York city and also on a part of non-grid road map of city of Carbondale, IL USA shows a much shorter average travel time compared to the existing popular algorithms based on dynamic traffic assignments (DTA). The proposed technique is also robust in the sense that even with 20% deviation from optimal assignment of traffic distribution at cross-points, we get significantly better results compared to the existing traffic distribution policies. We then propose a congestion control technique based on detouring of vehicles and show how variable link delay as a function of the volume of traffic flow through a link can be incorporated in our traffic distribution policy. Finally, we show how to extend our technique to consider a scenario with the destination point being anywhere on the grid, instead of being at the corner point.

We address the problem of evacuation of people in a natural disaster or some other emergency situations. In such a scenario, traffic from different parts of a city start moving simultaneously towards the nearest safe location. We propose here an optimal traffic routing algorithm in an 'almost' grid-structured network in a city to reach the safe location in minimum time, which is based on a novel technique of successively partitioning the network in suitable sub-networks to tackle the issue of missing links in the grid. Simulation results with the road network of Manhattan city show that our proposed technique performs better in terms of average time to reach the evacuation center than any of the existing techniques.

We address the problem of allocating channels in a hexagonal cellular network when device-to-device (D2D) communications are also present along with the usual cellular calls in the network. We formulate the channel allocation problem for this composite scenario of D2D and cellular communication in the network and find a lower bound on the required bandwidth in a 2-band buffering system in which interference does not extend beyond cells at distance two. Next we propose an elegant scheme for assigning channels and re-use them in the whole network in a systematic manner so as to satisfy homogeneous demands for the D2D communications as well as cellular calls. The assignment technique is very simple requiring O(n) computation time, n being the number of nodes in the network and needs a bandwidth marginally higher than the estimated lower bound.

In this paper, an energy-efficient communication scheme for low-power wireless networks is proposed which is based on encoding the messages by a novel source coding technique, called Dual-message Compression with Variable Null Symbol (DGVNS), followed by using the concept of Silent Communication. The source coding technique used in this scheme interleaves bits from two messages and encodes every two consecutive bits of this interleaved dual-message by one of four symbol values so that the overall message length is reduced by a factor of two. The transmitter is kept silent during the periods of the most dominant symbol which is dynamically changed. A hybrid modulation / demodulation technique using non-coherent FSK and ASK is used to have 43.46% energy savings on an average at the transmitter using a channel with Additive White Gaussian Noise (AWGN), and 50% energy savings at the receiver over the conventional Binary Frequency Shift Keying (BFSK), with equal likelihood of all possible strings of binary messages. Simulation results with real-life sensor data show that we can get still higher energy savings at the transmitter, ranging from about 54.1% to 58.9%. Also, the transmission time is reduced by a factor of two due to the reduced length of the encoded message. The scheme is suitable for multihop communication in low cost wireless sensor network applications.

We address the problem of optimally placing the access points in an ultra-dense 5G network to cover a given rectangular region so that every point in the region will be covered by at least one access point (AP) with minimal sum of total transmission power used by all APs. We analyze the wastage of transmission power for different types of placement of the APs with touching and intersecting circles for the full coverage of the rectangular region. We show that the minimum wastages in the inner bulk region with touching and intersecting circles are 81.4% and 20.77%, respectively. We then propose a systematic scheme to place the intersecting circles and show that for moderate size of the rectangle, the wastage due to the spill over of the circles at the boundary can be much higher that 20.77%, but when the side(s) of the rectangle is(are) very large compared to the radius r of the circles, the wastage asymptotically tends to around 20.86%. Also, we show that use of a few circles of smaller radius r' = 0.62r would significantly reduce the wastage even for a rectangle of small size and that would not require any additional bandwidth compared to the scheme for using all circles of the same radius r. The proposed placement scheme is very simple, elegant and effective in minimizing wastage of transmission power of APs as well as optimizing the bandwidth requirement through reuse of channels avoiding co-channel and adjacent channel interferences.

A significant number of applications in mobile transactions and wireless sensor networks (WSNs) are characterized by short duration sessions. Stream ciphers are a popular choice for ensuring the security of data communication sessions in such applications. In this paper, we propose a lightweight variant of the popular RC4 algorithm that is highly suitable for energy and computational resource constrained devices in wireless networks, as compared to RC4 and its variants (e.g., HC-128), Grain-128, etc., while being secure enough for a large class of short duration wireless application scenarios. We replace the PRGA keystream generation algorithm of RC4 by our proposed Lightweight Pseudo-Random Generation Algorithm (LPRGA). The test results for LPRGA on the NIST statistical test suite show that the output keystream generated by LPRGA is as random as the output generated by the PRGA of RC4, for keystream sequence lengths smaller than 30,000 bits - a requirement easily satisfied in nearly all mobile transactions, WSNs and ad hoc networks. The structural test results also prove the security strength of the proposed LPRGA. Furthermore, measurements of the period lengths of the LPRGA show that the proposed algorithm has a much larger period than the PRGA of RC4. We have also proved analytically the unpredictability of the proposed algorithm. Finally, for resource constrained wireless devices, we present the outline of a high performance hardware implementation with a significantly lower cost as compared to the conventional hardware implementations of RC4 for wireless networks. Our proposed hardware implementation is capable of throughput as high as one cipher byte per cycle of a 1 GHz clock using 65 nm fabrication technology.

This study aims to optimize patient flow in emergency departments (ED) while minimizing associated costs. In order to compare the effects of the optimization, a simulation model for emergency departments has been implemented using District Event Simulation (DES) and queuing theory, while for the optimization, Genetic Algorithm is used to find the best arrangements. Principally, a discrete event based, multi-class, multi-server queuing network is designed considering the emergency department as a set of stages each associated with a queue of patients waiting to be served. Each stage has multiple service providers such as Nurses, Doctors or other staff. We also classified patients passing through the stages according to their acuity level and personal characteristics. Then, a function is defined to measure the ED performance in respect to the calculated wait times and the cost. Finally, a customized genetic algorithm was developed to discover the best performance which reflects the best allocation of service providers to the different stages of the emergency department.

In this paper, we present a new approach to designing a scalable, hierarchical overlay P2P system which provides highly efficient data lookup operations as well fault tolerance. Instead of using a distributed hash table (DHT) based approach, we propose the use of Linear Diophantine Equation (LDE) as the mathematical basis to realize a hierarchical P2P architecture. LDE provides a significantly lighter weight mechanism to create and maintain the overlaid P2P structure as compared to DHT based schemes. To the best of our knowledge, ours is the first work that proposes the use of LDEs in designing P2P topologies. In our proposed hierarchical P2P architecture, the number of hops required to search for a resource is independent of the number of nodes/peers in the network n and is instead bounded by (1 + r/2), r being the number of distinct resource types. For most practical purposes, r is significantly smaller than n and hence our proposed architecture provides a highly efficient resource look-up procedure. We have also presented algorithms for handling of new resources and peers joining and leaving the P2P network and fault tolerance in the event of peers crashing or leaving.

RC4 is the most popular stream cipher in the domain of cryptology. In this paper, we present a systematic study of the hardware implementation of RC4, and propose the fastest known architecture for the cipher. We combine the ideas of hardware pipeline and loop unrolling to design an architecture that produces 2 RC4 keystream bytes per clock cycle. We have optimized and implemented our proposed design using VHDL description, synthesized with 130, 90, and 65 nm fabrication technologies at clock frequencies 625 MHz, 1.37 GHz, and 1.92 GHz, respectively, to obtain a final RC4 keystream throughput of 10, 21.92, and 30.72 Gbps in the respective technologies.

This paper presents a novel method for solving channel assignment problems (CAPs) in hexagonal cellular networks with nonhomogeneous demands in a 2-band buffering system (where channel interference does not extend beyond two cells). The CAP with nonhomogeneous demand is first partitioned into a sequence of smaller subproblems, each of which has a homogeneous demand from a subset of the nodes of the original network. Solution to such a subproblem constitutes an assignment phase, where multiple homogeneous demands are assigned to the nodes corresponding to the subproblem, satisfying all the frequency separation constraints. The whole assignment process for the original network consists of a succession of multiple homogeneous assignments for all the subproblems. Based on this concept, we present a polynomial time approximation algorithm for solving the CAP for cellular networks having nonhomogeneous demands. Our proposed assignment algorithm, when executed on well-known benchmark instances, comes up with an assignment which is always within about 6 percent more than the optimal bandwidth, but requires a very small execution time (less than 5 millisecond on a HPxw8400 workstation). The proposed algorithm is very much suitable for real-life situations, where fast channel assignment is of primary importance, tolerating, however, a marginal deviation (6 percent) from the optimal bandwidth.

We propose a redundant radix based number (RBN) representation for encoding and transmitting data for applications which typically utilize low cost devices and demand low power operations with simple modulation techniques like ASK, OOK and FSK. Coupled with silent periods for communicating the digit zero, this encoded communication scheme, called as RBNSiZeComm, provides a highly energy-efficient technique for data transmission. Considering an n-bit data representation and assuming that each of the 2nbinary strings is equally likely to occur, theoretically obtainable fraction of energy savings by using our proposed RBNSiZeComm transmission protocol is, on an average, 1 - n+2/4n. A hybrid modulation scheme using FSK and ASK with non-coherent detection based receiver for the RBNSiZeComm protocol has been presented. Assuming equal likelihood of all possible binary strings of a given length, there is nearly 53% savings in energy on an average at the transmitter relative to binary FSK, over additive white gaussian noise (AWGN) channels. Simulation results demonstrate that compared to binary FSK, our proposed implementation can extend the battery life of devices from about 33% to 62% on an average in applications like remote healthcare and wireless sensor networks for agriculture.

Abstract Efficient allocation of channels for wireless communication in different network scenarios has become an extremely important topic of recent research. The main challenge lies in the fact that the channel allocation problem is NP‐complete. Because of a maximum allowable time limit imposed in practical situations for allocation of channels, sometimes we may need to be satisfied with a near‐optimal solution. In this correspondence, we present a discussion on the various challenges and approaches that have been used by different researchers to solve the problem of channel allocation taking into account different interference issues and efficient utilization of available communication channels for cellular mobile (including multimedia communication) environment and cognitive radio based networks. Copyright © 2010 John Wiley & Sons, Ltd.

Applications requiring low power and quick turn on time (e.g., sensor networks) usually employ radios with only simple modulation techniques such as ASK, OOK and FSK. We present in this paper a non-coherent detection based transceiver implementation for the RBNSiZeComm protocol proposed. For a hybrid modulation scheme using FSK and ASK and assuming equal likelihood of all possible binary strings of a given length, we show that relative to binary FSK, there is a 41% savings in energy on an average at the transmitter, over additive white Gaussian noise (AWGN) channels. Furthermore, our simulation results demonstrate that compared to binary FSK, for wireless application scenarios where longevity of power supply is a major concern (e.g., remote healthcare, streaming multimedia and agriculture wireless sensor networks) our proposed implementation can extend the battery life of devices from about 33% to 61% on an average, for the different communication data types used in these applications. Coupled with the low cost and low complexity of the transceiver, these savings demonstrate the usefulness of RBNSiZeComm for applications involving low power wireless networks.

Wireless sensor networks typically require low cost devices and low power operations. Hence, such networks usually employ radios with only simple modulation techniques such as ASK, OOK and FSK. We propose a new energy efficient communication scheme for wireless sensor networks that is based on the ternary number system encoding of data. An efficient algorithm for conversion from binary to ternary and vice versa is used that does not involve any division or multiplication but only addition. Our Ternary with Silent Symbol (TSS) communication scheme is similar in concepts to the RBNSiZeComm protocol proposed. However, in contrast to RBNSiZeComm, TSS simultaneously saves energy at both the transmitter and receiver due to shortening of the transmission duration. We also propose a transceiver design that uses a hybrid modulation scheme utilizing FSK and ASK so to keep the cost/complexity of the radio devices low. With a non-coherent detection based receiver and assuming equal likelihood of all possible binary strings of a given length, there is a savings of about 20% in energy on an average at the transmitter compared to binary FSK, for additive white gaussian noise (AWGN) channels. Simultaneously, there is a savings of 36.9% at the receiver too, due to the reduced length of ternary encoded transmitted data, compared to binary encoding. Coupled with the low cost and low complexity of the transceiver, these results establish the effectiveness of TSS as a suitable candidate for communication in low power wireless sensor networks.