LoRaWANs, a widely accepted IoT connectivity solution, adopt a simple (ALOHA-like) MAC layer, enabling low-power communication at the cost of scalability due to packet collisions. Hence, current studies on LoRaWAN conclude that the network does not support dense deployments. Several alternative MACs are proposed but they stumble upon well-known limitations: time division eliminates the asynchrony of LoRa nodes but requires feedback from the gateways; carrier-sensing-based protocols are heavily constrained by the reduced sensing ranges of the devices, thus creating a large number of hidden terminals, leading to collisions.To enhance LoRaWAN to cater to both low- and high-density deployments, in this paper, we propose Spreading Factor MAC (SFMAC), a novel, practical, distributed, and energy-efficient MAC protocol. SFMAC, a channel-sensing-based MAC, takes an unconventional approach to eliminate hidden terminals – by operating with pairs of SFs, wherein the higher SF is used for channel sensing and the lower for data transmission. Bleeps are transmitted in the higher SF as they can be sensed at longer ranges. SFMAC does not require any change in hardware or the LoRaWAN protocol. We demonstrate that the fundamental trade-off made by SFMAC – utilizing two SFs per data transmission instead of using all for data – works extremely well due to the elimination of hidden terminals. Through real-world experiments on 30 SX1261 devices and data-driven ns-3 simulations, we showcase that SFMAC increases goodput and channel utilization by manifolds over state-of-the-art protocols such as p-CARMA, np-CECADA, and LMAC.

We present radio-frequency (RF) information harvesting, a chan-nel sensing technique that takes advantage of the energy in the wireless medium to detect channel activity at essentially no en-ergy cost. RF information harvesting is essential for event-driven wireless sensing applications using battery-less devices that har-vest tiny amounts of energy from impromptu events, such as op-erating a switch, and then transmit the event notification to a one-hop gateway. As multiple such devices may concurrently de-tect events, coordinating access to the channel is key. RF infor-mation harvesting allows devices to break the symmetry between concurrently-transmitting devices based on the harvested energy from the ongoing transmissions. To demonstrate the benefits of RF information harvesting, we integrate it in a tailor-made ultra low-power hardware MAC protocol we call Radio Frequency-Distance Packet Queuing (RF-DiPaQ). We build a hardware/software proto-type of RF-DiPaQ and use an established Markov framework to study its performance at scale. Comparing RF-DiPaQ against sta-ple contention-based MAC protocols, we show that it outperforms pure Aloha and 1-CSMA by factors of 3.55 and 1.21 respectively in throughput, while it saturates at more than double the offered load compared to 1-CSMA. As traffic increases, the energy saving of RF-DiPaQ against CSMA protocols increases, consuming 36% less energy than np-CSMA at typical offered loads.

Long-range wide-area network (LoRaWAN) is an energy-efficient and inexpensive networking technology that is rapidly being adopted for many Internet-of-Things applications. In this study, we perform extensive measurements on a new LoRaWAN deployment to characterise the spatio-temporal properties of the LoRaWAN channel. Our experiments reveal that LoRaWAN frames are mostly lost due to the channel effects, which are adverse when the end-devices are mobile. The frame losses are up to 70 percent, which can be bursty for both mobile and stationary scenarios. Frame losses result in data losses since the frames are transmitted only once in the basic configuration. To reduce data losses in LoRaWAN, we design a novel coding scheme for data recovery called DaRe that works on the application layer. DaRe combines techniques from convolutional and fountain codes. By implementing DaRe, we show that 99 percent of the data can be recovered with a code rate of 1/2 when the frame loss is up to 40 percent. Compared to the repetition coding scheme, DaRe provides 21 percent higher data recovery and can save up to 42 percent of the energy consumed on a transmission for 10-byte data units. We also show that DaRe provides better resilience to bursty frame losses.

The next frontier in communications is teleoperation – manipulation and control of remote environments. Compared to conventional networked applications, teleoperation poses widely different requirements, ultra-low latency (ULL) being the primary one. Teleoperation, along with a host of other applications requiring ULL communication, is termed as Tactile Internet (TI). A significant redesign of conventional networking techniques is necessary to realize TI applications. Further, these advancements can be evaluated only when meaningful performance metrics are available. However, existing TI performance metrics fall severely short of comprehensively characterizing TI performance. In this paper, we take the first step towards bridging this gap. To this end, we propose a method that captures the fine-grained performance of TI in terms of delay and precision. We take Dynamic Time Warping (DTW) as the basis of our work and identify whether it is sufficient in characterizing TI systems. We refine DTW by developing a framework called Effective Time- and Value-Offset (ETVO) that extracts fine-grained time and value offsets between input and output signals of TI. Using ETVO, we present two quantitative metrics for TI – Effective Delay-Derivative (EDD) and Effective Root Mean Square Error. Through rigorous experiments conducted on a realistic TI setup, we demonstrate the potential of the proposed metrics to precisely characterize TI interactions.

High accuracy and device-free indoor localization is still a holy grail to enable smart environments. With the growing privacy concerns and regulations, it is necessary to develop methods and systems that can be low-power, device-free as well as privacy-aware. While IR-based solutions fit the bill, they require many modules to be installed in the area of interest for higher accuracy, or proper planning during installation, or they may not work if the background has multiple heat-emitting objects, etc. In this paper, we propose a custom-built miniature device called LOCI that uses IR sensing. One unit of LOCI can provide three-dimensional localization at best. LOCI uses only a thermopile and a PIR sensor built within a 5x5x2 cm3module. Since IR-based sensing is used, LOCI consumes around 80 mW. LOCI uses analog waveform from the PIR sensor with the gain of the PIR sensor dynamically controlled through software in real-time to simulate spatial diversity. LOCI proposes low-complexity techniques with sensor fusion to eliminate the noise in the background, which has not been handled in previous works even with sophisticated signal processing techniques. Since LOCI uses raw data from the thermopile, the computations are power-efficient. We present the complete design of LOCI and the proposed methodology to estimate height and location. LOCI achieves accuracies of sub-22 cm with a confidence of 0.5 and sub-35 cm with a confidence of 0.8. The best-case location accuracy is 12.5 cm. The accuracy of height estimation is within 8 cm in majority cases. LOCI can easily be extended to recognize activities.

Global Positioning System is a widely adopted localization technique. With the increasing demand for small satellites, the need for a low-power GPS for satellites is also increasing. To enable many state-of-the-art applications, the exact position of the satellites is necessary. However, building low-power GPS receivers which operate in low earth orbit pose significant challenges. This is mainly due to the high speed (~7.8 km/s) of small satellites. While duty-cycling the receiver is a possible solution, the high relative Doppler shift between the GPS satellites and the small satellite contributes to the increase in Time To First Fix (TTFF), thus increasing the energy consumption. Further, if the GPS receiver is tumbling along with the small satellite on which it is mounted, longer TTFF may lead to no GPS fix due to disorientation of the receiver antenna. In this paper, we elucidate the design of a low-cost, low-power GPS receiver for small satellite applications. We also propose an energy optimization algorithm called F3to improve the TTFF which is the main contributor to the energy consumption during cold start. With simulations and in-orbit evaluation from a launched nanosatellite with our μGPS and high-end GPS simulators, we show that up to 96.16% of energy savings (consuming only ~ 1/25th energy compared to the state of the art) can be achieved using our algorithm without compromising much (~10 m) on the navigation accuracy. The TTFF achieved is at most 33 s.

Many IoT applications require the knowledge of crowd distribution, particularly in indoor scenarios. To this end, we leverage the lighting grid infrastructure in buildings by using smart light bulbs, which can include variety of sensors, in these grids. The exponentially increasing adoption of smartphones and the Wi-Fi infrastructure has motivated us to tackle this problem using Wi-Fi. As we seek a solution that works in many buildings, relying on active user participation or installing apps is not an option. Therefore, we need a Wi-Fi based crowd distribution estimation technique that is non-participatory and non-intrusive, and works with very few Wi-Fi packets generated by users' smartphones sporadically. We approach the problem by analyzing the Wi-Fi packets for counting people (smartphones) and estimating their position within a pre-defined accuracy. To this end, extensive experiments are conducted in a real-world testbed with controlled settings as well as in test setups in office spaces with no control. We propose improvised counting techniques that results in people counts close to 75% of the ground truth. We further propose improvements to range-free localization techniques to refine the position estimation accuracy and reduce the execution time. Our algorithm estimates the location with an accuracy of 2m 74% of the time, when Wi-Fi sniffers are placed in bulbs every 4m in the grid.

Many Internet of Things smart-* applications are being powered solely through ambient energy-harvested energy. These applications require periodic data collection with low latency and high reliability. Since the energy is harvested in small amounts from ambient sources and is stochastic in nature, it is extremely challenging to achieve low latency and high reliability for such applications. To this end, we propose a distributed, energy-management module called ReNEW, for Constructive Interference (CI) based protocols that utilizes the available energy effectively in order to achieve our target of increased reliability in EH-WSN, especially in the low harvesting regimes. We choose CI-based protocols to leverage the low latency guarantees. Specifically, we propose a Markov decision model to maximize the energy utility in the infinite horizon by allocating energy optimally. To this end, we also propose a threshold optimal policy. As we find that just a energy scheduler cannot achieve the goal, we also propose distributed techniques to conserve energy on the redundant nodes in the network, and dynamically activate them based on feedback. We also improve the performance of CI by adapting the transmit powers on nodes. We implement and evaluate ReNEW on Indriya testbed for real-world scenarios. We show that in a network of 20 source nodes out of the 30 nodes in the network can perform periodic data collection with an improvement of 2.5 times higher packet reception ratio as compared to LWB. This is one of the worst case scenarios as the harvested energy is as low as 50uJ/s and packets of size 100 B is sent every 30 s. Furthermore, in this scenario, ReNEW saves around 25% higher residual energy on the average as compared to the standard LWB. In a nutshell, by integrating ReNEW with CI based protocols, we enable guaranteed latency and increased reliability for the batteryless EH-WSNs.

Two nanosatellites recently launched into space had issues with respect to its stabilization, power and orientation. The signals were intermittent, and amateur radio enthusiasts around the globe were requested to observe the satellites so as to get their health information. As decoding the received signals required proprietary hardware (that could not be sent to everyone), amateur radio receivers recorded the signal using Software Defined Radios (SDRs) and sub-sampled the carrier signals to make it easy to share. The captured signals, modulated using binary Frequency Shift Keying (FSK), included noise and more importantly the frequency shifts due to Doppler, caused by the speed of the satellites (of about 7.8 km/s), thus making decoding a major challenge even for the designated proprietary receivers (failed in some cases). As the existing FSK methods did not work effectively, we were motivated by this challenge to design an effective FSK decoder that works in the presence of Doppler and noise. In this paper, we propose Teager Energy Decoder (TED) based on Teager Energy Operator to decode such Doppler and noise influenced sub-sampled data. TED does not need any Doppler correction mechanisms and can dynamically adapt to the changing frequency shifts. We evaluate TED using simulation as well as from the signals from those two satellites. We show that TED performs better than COTS transceivers and available GNU-radio-based solutions using SDRs. TED is low-complexity algorithm, O(N2), and has been prototyped on a low-power micro-controller. TED can be easily adopted on satellites to decode signals for space Internet of Things applications.

The IEEE “Tactile Internet” (TI) Standards working group (WG), designated the numbering IEEE 1918.1, undertakes pioneering work on the development of standards for the TI. This paper describes the WG, its intentions, and its developing baseline standard and the associated reasoning behind that and touches on a further standard already initiated under its scope: IEEE 1918.1.1 on “Haptic Codecs for the TI.” IEEE 1918.1 and its baseline standard aim to set the framework and act as the foundations for the TI, thereby also serving as a basis for further standards developed on TI within the WG. This paper discusses the aspects of the framework such as its created TI architecture, including the elements, functions, interfaces, and other considerations therein, as well as the novel aspects and differentiating factors compared with, e.g., 5G Ultra-Reliable Low-Latency Communication, where it is noted that the TI will likely operate as an overlay on other networks or combinations of networks. Key foundations of the WG and its baseline standard are also highlighted, including the intended use cases and associated requirements that the standard must serve, and the TI's fundamental definition and assumptions as understood by the WG, among other aspects.

The constructive interference (CI) phenomenon has been exploited by a number of protocols for providing energy-efficient, low-latency, and reliable data collection and dissemination services in wireless sensor networks. These protocols consider CI to provide highly reliable packet delivery. This has attracted attention to understand the working of CI; however, the existing works present inconsistent views. Furthermore, these works do not study in the real-world settings where the physical conditions of deployment and unreliable wireless channels also impact the performance of CI. Therefore, we study the phenomenon of CI, considering a receiver's viewpoint and analyze the parameters that affect CI. We validate our arguments with results from extensive and rigorous experimentation in real-world settings. This paper presents comprehensive insights into the CI phenomenon. With the understanding, we develop the destructive interference-based power adaptation (DIPA), an energy-efficient and distributed algorithm, that adapts transmission power to improve the performance of CI. Since CI-based protocols cannot have an explicit acknowledgment packet, we make use of destructive interference on a designated byte to provide a feedback. We leverage this feedback to adapt transmission powers. We compared CI with and without DIPA in two real-life testbeds. On one testbed, we achieve around 25% lower packet losses while using only half of its transmission power for 64-B packets. On the other testbed, we achieve 25% lower packet losses while consuming only 47% of its transmission power for 128-B packets. Existing CI-based protocols can easily incorporate DIPA into them to achieve lower packet losses and higher energy efficiencies.

Progress in low power miniaturized electronics and wireless technologies have enabled many innovative applications. Of particular interest is the Internet of Things (IoT) that has dominated the world of ICT in the last half a decade enabling many smart systems and applications. At the same time, we also see much enthusiasm with respect to space missions and applications including terrestrial applications, apart from exploring the universe. We believe that innovations in the domain of IoT will significantly influence the space related activities -- both research and development. In this article, we chart out the innovations in space and the vision with respect to embedded and wireless systems for space applications. In particular, we bring in the notion of Sensor Wireless Actuator Networks in Space (SWANS) and Space Pixels to explain IoT in space. We explain with examples what we envision for the next decade and also the challenges therein. We briefly put forth our four major targets in the next five years.

Ambient energy-harvesting technology is a promising approach to keep wireless sensor networks (WSNs) operating perpetually. Depending on the harvesting source nodes can either be active (alive) or inactive (dead) at any instant in such Energy-Harvesting WSNs (EH-WSNs). Thus, even in a static deployment of EH-WSNs, the network topology is no longer static. A popular method to increase energy-efficiency in WSNs is by employing topology control algorithms. Most of the topology control algorithms in the literature cannot handle the situation when nodes have different energy-levels, and when number of active nodes varies with time in EH-WSN. To address this issue, we present two localized energy based topology control algorithms, viz., EBTC-1 and EBTC-2. EBTC-1 is for convergecast applications of WSNs and EBTC-2 is for a generic scenario where all nodes are required to be connected. While typical topology control algorithms select a particular number of neighbors, the distinguishing feature of both these algorithms is that they select neighbors based on energy-levels, and render the global topology strongly-connected. Simulation results confirm that EBTC-1 and EBTC-2 reduce the transmission power and they let nodes have neighbors with high remaining energy. Results show that our proposed algorithms increase at least 33% in the remaining energy per neighbor. In addition, in terms of energy consumption and fault-tolerance, our proposed algorithms typically achieve 1-connected topology using 74% less energy compared to K-Neigh.

Constructive Interference (CI) phenomenon has been exploited by Glossy, a mechanism for low-latency and reliable network flooding and time synchronization for wireless sensor networks. Recently, CI has also been used for other applications such as data collection and multicasting in static and mobile WSNs. These applications base their working on the high reliability promised by Glossy regardless of the physical conditions of deployment, number of nodes in the network, and unreliable wireless channels that may be detrimental for CI. There are several works that study the working of CI, but they present inconsistent views. We study CI from a receiver's viewpoint, list factors that affect CI and also specify how and why they affect. We validate our arguments with results from extensive and rigorous experimentation in real-world settings. This paper presents comprehensive insights into CI phenomenon. With this understanding, we improve the performance of CI through an energy-efficient and distributed algorithm. We cause destructive interference on a designated byte to provide negative feedback. We leverage this to adapt transmission powers. Compared to Glossy, we achieve 25% lesser packet losses while using only half of its transmission power.

Pyroelectric Infra-Red (PIR) sensors are used in many applications including security. PIRs detect the presence of humans and animals from the radiation of their body heat. This could be used to trigger events, e.g., opening doors, recording video, etc. PIRs are used widely because of their low power consumption.

Ambient energy harvesting for Wireless Sensor Networks (WSNs) is being pitched as a promising solution for long-lasting deployments in various WSN applications. However, the sensor nodes most often do not have enough energy to handle application, network and house-keeping tasks because amount of energy harvested highly varies spatially and temporally. Moreover the ambient source cannot be assumed to be continuously available. When harvested energy is in excess, it is desirable that the nodes take up higher loads. The nodes should switch to highly energy efficient schemes when the energy is not sufficient. Hence harvesting-aware scheduling of tasks is required. The two most important challenges for harvesting-aware scheduling are (a) to determine the amount of energy to be expended in a time slot, and (b) to utilize this energy for execution of tasks maximally. To increase energy utilization for task execution, we decompose application level tasks into subtasks, some of which can be executed concurrently. In this article, we propose a dynamic optimization model, based on Markov Decision Process (MDP) that takes into account priorities and deadlines of the tasks, and stored and harvested energy to derive an optimal scheduling policy. Since the complexity of the MDP is intractable in realtime, we propose a greedy scheduling policy. We compare its performance with the optimal policy.

In data gathering wireless sensor network applications, data correlation among the sensor nodes have been utilized to extend network lifetimes. It has been shown that the data correlation also exists between nodes that are far away, contrary to the assumption that correlation decreases as a function of distance. Therefore, it is possible to group the nodes based on the correlation among their data regardless of their location. Given that data from one active node per group is sufficient to reconstruct the sensed data for the remaining sensor nodes, most of the nodes can be kept in low-power sleep mode. However, only few active nodes will usually create a disconnected network, and hence failing the purpose of the deployment. In this paper we formalize this problem, referred to as Sleep-route, of selecting the minimum number of connected active nodes that are sufficient to predict the sensed data for remaining sleeping nodes with high accuracy. We prove that the problem is NP-hard. Thus, we develop a greedy algorithm, Sleep-route heuristic that provides near-optimal solutions. Using Contiki-based simulations, we show that our scheme can extend network lifetime up to 42% as compared to the state-of-the-art solutions.

Homes, offices and vehicles are getting networked. This will enable context aware, autonomous operation of many support systems that could be controlled remotely. To achieve this there would be a large number of tiny devices - sensors and actuators - which are networked and they are termed generally as Internet of Things (IoT) devices. In future, they will be powered through harvested energy from the ambience to enable perennial lifetime and minimal manual maintenance. Some examples of energy sources are photovoltaic panels and piezoelectric crystals. Several challenges arise due to the nature of sources of energy. One of these challenges is that the devices (nodes) leave and re-enter networks due to fluctuating availability of harvested energy. As a result, the neighbor table maintained at each node changes quite often leading to complications in forming and maintaining routes. In fact initial neighbor discovery (ND) itself is a difficult task. Further, usage of directional antennas would increase the time taken to complete ND. We study such a network through exhaustive simulation study considering various parameters. We demonstrate the benefits and challenges of using directional antennas for ND. We present a scheme that nodes could use to discover their neighbor during initial deployment and another scheme that could be used for subsequent discovery on re-entry into the network. We show that a dedicated ND protocol is necessary for energy harvesting networks and that directional ND is beneficial in these networks under some circumstances.

IEEE 802.22 is the first standard to uitilize cognitive radio technology for wireless regional area networks (WRANs). It has adopted a cellular topology containing one base station (BS) and multiple customer premises equipments (CPEs) in a cell. It covers a very large area with radius ranging up to 100 km. Orthogonal frequency-division multiple access (OFDMA) system is employed and it is further slotted in time-domain. In one slot only one CPE can be allocated, and every intra-cell packet needs to be routed through the BS. This point-to-multi-point structure significantly limits the network capacity in the case of CPE-CPE communication, which is predicted to happen, and even the use of OFDMA does not help much. Therefore, peer-to-peer WRAN (P2PWRAN) has been proposed to support direct intra-cell communication in order to extend the network capacity. In this paper, the IEEE 802.22 OFDMA system is adapted to P2PWRAN to support direct CPE-CPE communications. The downstream burst allocation in P2PWRAN is similar to the OFDMA system of IEEE 802.16, which has been widely studied in the literature. Therefore, in this paper we look at the unexplored upstream burst allocation where slots can be reused among CPEs and the BS with power control mechanisms. We propose a burst allocation algorithm that maximizes the network capacity greedily. The algorithm is examined under various conditions such as, number of CPEs, size of requests, length of US subframes and type of requests (CPE-BS or CPE-BS). We also show that our algorithm performs better than the existing solutions.

IEEE 802.22 is proposed for reusing the TV channels with cognitive radio technology to build Wireless Regional Area Networks (WRANs). The cellular topology of a WRAN makes the spectrum management easy. However, this topology reduces the network capacity significantly, because in one slot only one user can be allocated with a channel. Therefore, Peer-toPeer WRAN (P2PWRAN) is proposed, in which direct CPE(Consumer Premises Equipment)-to-CPE intra-cell communication is supported. While increasing the network capacity significantly, reducing the total energy consumption is a challenge.The energy efficiency of nodes in the standard for WRAN is difficult to improve, since the transmission distance of nodes to the BS is relatively static. P2PWRAN enables to achieve higher energy efficiency through better possibilities of channel allocation. Channel allocation influences energy consumption and network capacity significantly. Channel allocation also affects the upper layers, for example the routing protocol. Therefore, guaranteeing the network performance and fairness amongst CPEs, while achieving green networks, needs cross-layer design. In this paper, we define the channel allocation problem in P2PWRAN and we recognize it as a Multi-objective Quadratic Programming (MOQP) problem. An Energy-aware Channel Allocation (ECA) algorithm is proposed for exploiting the P2PWRAN paradigm to achieve the lower communication energy consumption and higher network energy efficiency and throughput than simple greedy policies. ECA jointly considers the network layer and Media Access Control (MAC) layer. By controlling the parameters in ECA, the fairness of channel allocation can also be guaranteed.

Peer to peer wireless regional area network (P2PWRAN) is proposed as an extension to support peer to peer communication based on IEEE 802.22 [1]. Multiple channel allocation and reuse of channels in the same time slot in P2PWRAN significantly increase the network capacity compared to standard IEEE 802.22 networks. One of the key issues in bringing P2PWRAN into reality is building the interference map. The concept of interference map/mapping has been mentioned in literature however, how to build an interference map is still an open issue. Therefore, we propose a simple and self-adapting interference map building protocol (SIMBP) for P2PWRAN, which can also be used in other multi-channel wireless networks with minor modifications. The simulation results show that SIMBP converges under the P2PWRAN setting, and with number of available channels and growing number of nodes, the capacity of the network is reached eventually.

Wireless Regional Area Networks(WRAN), IEEE 802.22 standard, adopts a centralized cellular topology including base station (BS) and customer-premise equipments (CPEs). However this may lead to limited network capacity, since every CPE needs to communicate to the BS and only one channel can be used to communicate in the whole cell per time slot with one BS antenna. Peer to Peer WRAN (P2PWRAN) was proposed [3] to circumvent this, where CPEs can communicate with each other directly. P2PWRAN increases network capacity compared to the standard WRAN because of spatial reuse. Multiple communication channels can be simultaneously allocated and reused in one time slot by the BS and multiple CPEs. In IEEE 802.22b [4], a standard in progress, peer to peer communication plays an important role for enabling smart grids. Channel allocation influences the network performance significantly, therefore, we formulate the spectrum allocation problem in P2PWRAN as a quadratically constrained programming (QCP) problem. It is also proved as a computationally hard problem. The Greedy Coloring Algorithm (GCA) is examined in P2PWRAN channel allocation, and the results show that it may cause severe unfairness in allocation of channels. Thus a Fair Greedy Coloring Algorithm (FGCA) is proposed to guarantee a fair allocation by queuing flows considering previous allocations. However, FGCA guarantees fairness but leads to decrease in performance of P2PWRAN. Therefore, a Trade-off FGCA (TFGCA) is proposed considering fairness and network performance at the same time during allocation. Simulation results show that with the adjustment of two factors in TFGCA, network performance and fairness can be balanced.

Cognitive Radios (CRs) address spectrum scarcity and under-utilization of the spectrum. Allocating spectrum to CR nodes in a network is neither easy nor straight-forward since spectrum availability is space and time-varying. The Link layer always sets up communication between nodes in a CR ad hoc network by allocating the available spectrum suitably. In a time-slotted model, allocation of channels amongst CR nodes is a NP complete problem. Moreover, since the availability of spectrum is time varying, all the nodes in the network may not be allocated sufficient resources. Thus there is always a possibility that a node may starve compared to its counterparts. In this article, we address the issue of fairness in a CR ad hoc network and propose novel distributed heuristics to allocate spectrum fairly. In literature, max-min, max-sum and max-proportional fairness based schemes are proposed to provide fairness in these CR ad hoc networks. We compare our heuristic results with these schemes, and discuss why our method is significantly better.

Cognitive radios (CRs) address the problems of spectrum scarcity and under-utilization of the spectrum. However, realizing a CR network is neither easy nor straight-forward. The link layer in CR ad hoc networks is responsible for choosing suitable channels, out of the available channels, for setting up communication between nodes. However, the selection of channels amongst the CR nodes in the network is proven to be NP-complete. The need of maximizing the spectrum efficiency in a fair way can be modeled as a graph coloring problem. An edge coloring heuristic and a clique determination heuristic algorithms are proposed in this article. We compare the results of these heuristics with the algorithm proposed in. We also compare the spectrum utilization in all these algorithms.

Cognitive Radios (CRs) address spectrum scarcity and under-utilization of the spectrum. However, realizing a CR network is neither easy nor straight-forward. In particular the link layer should facilitate setting up of communication between nodes enabling sharing of channels, while maximizing the spectrum utilization. We address the problem of allocation of channels to CR nodes. For time-slotted model, allocating the channels among CR nodes is an NP complete problem. We propose novel distributed heuristics, one based on clique sets called Clique Based Heuristic and the second one is a low complexity, locally adapting Localized Heuristic; both use local control channel. We compare the results of these heuristics with the optimal and a distributed graph coloring algorithm proposed in the literature. We also compare the spectrum utilization and overheads for all these algorithms.

VoIP packets, when transported over the Internet, experience loss and variable delay. The effect of the network not only depends on the background flows but also on the parameters of VoIP packets itself, such as VoIP packet size and the packet generation intervals. While higher sized packets experience more losses, they experience less delay jitter and handling them is thus easy at the playout buffer. To investigate the effect of various network conditions on VoIP session holistically, we present a complete end to end study considering various states of the underlying network. We present as a case study of G.711 coded packets generated at 20 and 40 ms intervals for comparison. While packets carrying 20 ms data are better when the network is loaded, 40 ms packetization is favored when the network is not saturated. This affects the jitter and loss thus affecting the quality. We explain this trade-off using mean opinion scores.