Wireless sensor networks (WSNs) consist of power-constrained sensor nodes deployed for various data collection operations in real-world settings. The WSN nodes collect real-time data and send it to a data processing unit (DPU) for in-depth analysis of the collected data with multihop relaying. For sparsely deployed WSNs, data collected from nodes many hops away from the DPU suffer significant delays, thus making such deployments unsuitable for delay-critical applications. However, adding shortcut edges (SEs) directly to the DPU can alleviate the end-to-end transmission delay by incorporating small-world properties. In this paper, we analytically find the optimal locations of a few SEs on a finite-sized linear WSN. Moreover, we also characterize the associated tradeoff in transmit power for using these SEs in the existing linear WSN.

Real-world Machine-to-Machine (M2M) networks comprise of power-constrained sensor nodes to collect data of interest and send it to data aggregators for further processing using multi-hop relaying which increases end-to-end transmission delay. However, in many real-world application scenarios such as low latency communication in a 5G network, there is a strict delay deadline that has to be met. In this paper, we propose Constrained Link Addition Using high Sensor nodes (CLAUSe) to efficiently construct a few long-ranged links among the chosen high sensor nodes (sensor nodes with at least two interfaces) to reduce end-to-end hop distance in a sparse random M2M network setting, thereby, incorporating the small-world characteristics.

Internet of Things (IoT) refers to the concept of enabling Internet connectivity and associated services to nontraditional computers formed by integrating essential computing and communication capability to physical things for everyday usage. Security and privacy are two of the major challenges in IoT. The essential security requirements of IoT cannot be ensured by the existing security frameworks due to the constraints in CPU, memory, and energy resources of the IoT devices. Also, the centralized security architectures are not suitable for IoT because they are subjected to single point of attacks. Defending against targeted attacks on centralized resources is expensive. Therefore, the security architecture for IoT needs to be decentralized and designed to meet the limitations in resources. Blockchain is a decentralized security framework suitable for a variety of applications. However, blockchain in its original form is not suitable for IoT, due to its high-computational complexity and low scalability. In this article, we propose a sliding window blockchain (SWBC) architecture that modifies the traditional blockchain architecture to suit IoT applications. The proposed SWBC uses previous $(n-1)$ blocks to form the next block hash with limited difficulty in proof-of-work (PoW). The performance of SWBC is analyzed on a real-time data stream generated from a smart home testbed. The results show that the proposed blockchain architecture increases security and minimizes memory overhead while consuming fewer resources.

Corporate governance has a significant impact not only on the behavior and performance of a corporation but also on the functioning of other corporations, entrepreneurialism in the economy, and the working of capital markets. One way of looking at the effects of corporate governance on company performance is to study the contributions of the corporate board of directors. In this article, we explore the network of the director boards for the top Indian corporations to better understand the effects of the interlocking of management boards when the financial performance is considered. To study the corporate networks, we collected and analyzed relevant data set of the top 150 Indian companies on the basis of the maximum revenue generation. We find that the debt-to-equity ratio (D/E), on average, tends to decrease as the measure of the degree centrality of certain corporations increases. Furthermore, we study a modularity maximization-based community structure of the network of director boards to better comprehend the interconnections of the Indian corporates. Moreover, the underlying relationship between the modularity and the corporate performance is also analyzed, and it can be observed that most of the top Indian corporations, with low net current asset value per share, belong to the larger communities.

A novel framework is proposed for software defined wireless mesh networks involving mobile switches and controllers operating under in-band control in order to self-configure depending on the network dynamics. Besides the addition/removal of nodes (including switches and controllers) to/from the network in real-time, the problem becomes more challenging for switches to select an appropriate controller from multiple physical controllers. Therefore, first we design a resource discovery scheme to address the dynamic addition and removal of nodes with a software defined optimized link state routing (SD-OLSR) protocol. Apart from resource discovery, SD-OLSR captures the network dynamism and provides a global network view to the controller. Further, two controller handoff schemes, controller-initiated handoff (CIH) and switch-initiated handoff (SIH), are designed for switches to efficiently handover to a suitable controller. The framework and handoff schemes are tested using a software defined wireless mesh network testbed involving mobile switches and controllers operating under in-band control. The results show that SIH performs better in terms of SDN control overhead and PacketIn-FlowMod delay, while CIH outperforms SIH in terms of the number of handoffs and controller handoff time. A fair trade-off between the number of handoffs and the desired performance metric can be achieved by tuning the handoff threshold in both CIH and SIH schemes. As an added benefit, our framework provides better load sharing among the controllers in terms of flow-rule requests.

A novel framework, Medium-Term Disruption Tolerant Software Defined Network (MDT-SDN), is proposed to handle medium-term disruptions of the order 10 seconds to 6 minutes. Such medium-term disruptions are crucial for the next generation wireless networks that use TCP/IP protocol stack, where the existing disruption tolerant approaches may under-perform due to resource constraints. MDT-SDN enables network control with an additional STORE action which exploits the nodes' memory for buffering packets within the TCP/IP stack during link disruptions and forwards them as the links become alive. First, we model the network with medium-term disruptions using temporal graphs and design an Earliest Arrival Path with Minimal Storage Time (EAPMST) controller algorithm to demonstrate the MDT-SDN framework. The framework is realized in a software defined wireless mesh network testbed, using in-band control, involving mobile nodes with three mobility models: (i) stationary nodes, (ii) group mobility, and (iii) random mobility. Experimental results with four application protocols justify the efficacy of MDT-SDN in providing storage control and additional performance benefits. MDT-SDN along with EAPMST improves the throughput beyond 25% with random mobility model and is capable of carrying packets and maintaining sessions during medium-term disruptions using the existing TCP/IP stack. The use of EAPMST reduces packets' buffering time by 24.45% in group mobility while the buffering time increases in random mobility by 5.82%. However, EAPMST significantly reduces the buffer occupancy by 60.28% and 44.49% for group and random mobility, respectively.

The task of rescue and information gathering has been a major challenge in disaster-prone areas such as shanty towns, where a high density of population are served by poor infrastructure. Inefficient planning becomes a major problem for cities, especially in developing and least developed countries. In this paper, we address the problem of information gathering from a shanty town using mobile data collecting agents (MDCs) assuming neither location map nor communication infrastructure are available. Considering the heterogeneity in the types of roads and MDCs, we define five hybrid mobility models for information gathering: (i) Path Type with Restricted Movement, (ii) Path Type with Wait, (iii) Repetitive Highway with Restricted Movement, (iv) Repetitive Highway with Wait, and (v) Repetitive Highway with Nearest Point. In addition, we define two handoff protocols, Deposit Data handoff and Receive Data handoff, for the MDCs to transfer the gathered information to the Depot. For analyzing the performance, we simulate the mobility models using Urban DTN simulator with the map of shanty town Dharavi, India. The results show that the proposed mobility models provide delivery ratio beyond 50% and Repetitive Highway with Nearest Point being the highest with 74%, with reduced inter-meeting time.

Present day malicious software, often encountered in an Internet-enabled electronic system, turn to be extremely difficult to be detected by the existing malware detection solutions. In this paper, we introduce a novel malware detection strategy, Memory management with API CAll mIning (MACA-I), that efficiently detects malware based on the dynamic analysis. MACA-I analyzes API calls that are responsible for accessing the system memory and, thereby, generates required features by observing the transitions of memory management APIs as well as the allocated memory block space during the runtime. We find that MACA-I is approximately 95.45% accurate while detecting malware programs on the basis of system memory-related runtime behavior.

To investigate reported emergency incidents and provide better situational awareness during an emergency response effort in a shanty town, we envision the use of volunteers with networked sensing devices employed as Mobile Data Collectors (MDCs). These MDCs are heterogeneous depending upon the type of roads they can access. They gather information about events reported dynamically at random and relay it to central command center. We consider the problem of minimizing the Travel Time of such heterogeneous volunteer MDCs and maximizing the gathering of event data before its expiry time. We model this problem as a Dynamic Vehicle Routing Problem with Time Windows (DVRPTW), which reduces to a Combinatorial Optimization Problem and is NP-Hard to solve. In this paper, we developed two algorithms, Minimum Deviated Walk and Ortho Walk, to dynamically route or reroute the path of these MDCs to capture the data efficiently. We tested the effectiveness of these algorithms with three different classes of MDCs on simulated non- deterministic random sets of events applied to a real road map of Dharavi, a shanty town in Mumbai, India. We show that both these algorithms are capable of capturing 20% more data than a naive algorithm as well as more than 90% of the events generated within a specified time.

We propose a novel power saving strategy called Sleep during Neighbor-Addressed Frame (SNAF) for improving energy efficiency of IEEE 802.11 based wireless networks. IEEE 802.11 (Wi-Fi) radios that employ SNAF mode can turn OFF their wireless transceivers (i.e., put radios in sleep mode) within specific periods of neighbor-addressed frames while they are being received. The sleep duration of transceivers is easy to determine with no loss of packet's critical control information. The proposed SNAF mode operation does not have any negative effect on network throughput and even complements Power Saving Mode (PSM) available in 802.11 standard. We further propose GreenFrame format for next generation wireless networks. In experiments conducted in wireless LAN scenarios, we observed savings as much as 57.8% when we implement SNAF mode in 802.11 standard and up to 49.5% when we implement SNAF mode in 802.11 PSM.

In this paper, we investigate the machine learning based strategies for dynamic channel selection in Cognitive Access Points (CogAPs) of WLANs. We employ Multi-layer Feedforward Neural Network (MFNN) models that utilize historical traffic information from network environment for learning the influence of spatio-temporal-spectral factors on the network and then predicting future traffic loads on each of the channels. Based on the future traffic loads, CogAP chooses the best channel for serving wireless clients. An important factor is the time scale of traffic prediction. We construct three kinds of traffic predictors that predict traffic at different time scales: MLP (Minute Level Prediction), MILP (Minute Interval Level Prediction), and HLP (Hourly Level Prediction) schemes and study their prediction accuracy. Experiment results show that MFNN predictors perform better than traditional autoregressive models in terms of prediction accuracy. In addition to accurate prediction, another factor that influences the design of cognitive network channel selection is the impact of channel selection strategy on the transport layer performance. We, therefore, conduct performance studies on the TCP throughput achieved on the above mentioned cognitive channel selection strategies. The MFNN predictors will also help CogAP to find and switch to the optimal channel, leading to a higher and more sustained throughput.

Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios that apply cognition only at the physical layer. Designing a cognitive network is challenging since learning the relationship between network protocol parameters in an automated fashion is very complex. We propose to use Bayesian Network (BN) models for creating a representation of the dependence relationships among network protocol parameters. BN is a unique tool for modeling the network protocol stack as it not only learns the probabilistic dependence of network protocol parameters but also provides an opportunity to tune some of the cognitive network parameters to achieve desired performance. To the best of our knowledge, this is the first work to explore the use of BNs for cognitive networks. Creating a BN model for network parameters involves the following steps: sampling the network protocol parameters (Observe), learning the structure of the BN and its parameters from the data (Learn), using a Bayesian Network inference engine (Plan and Decide) to make decisions, and finally effecting the decisions (Act). We have proved the feasibility of achieving a BN-based cognitive network system using the ns-3 simulation platform. From the early results obtained from our cognitive network approach, we provide interesting insights on predicting the network behavior, including the performance of the TCP throughput inference engine based on other observed parameters.

In this paper, we present an application of the Cognitive Networking paradigm to the problem of development of autonomous Cognitive Access Point (CogAP) for small scale wireless network environments such as Wi-Fi hotspots and home networks. In these environments we typically use only one AP per service provider/residence for providing wireless services to the users. However, note that larger number of APs from multiple service providers/residences vie for bandwidth in any geographic region. Here we can reduce the cost of autonomic network control by equipping the same AP with a cognitive functionality. We first present architecture of our autonomous CogAP. Then we introduce our algorithmic solution, in which a Neural Network-based traffic predictor makes use of historical traffic traces to learn network traffic conditions and predicts traffic loads on each of 802.11 b/g channels. The cognitive decision engine makes use of traffic forecasts to dynamically decide which channel is best for CogAP to operate on for serving its clients. One of the challenges in autonomous cognitive decision making is the computation resource constraints in today's embedded APs. We have built a prototype CogAP device using cognitive software modules and off-the-self hardware components. We carried out performance evaluation of the proposed CogAP system by conducting experimental measurements on our testbed platform; the obtained results show that the proposed CogAP is effective in achieving performance enhancements with respect to state-of-the-art channel selection strategies.

In this paper, we present an application of the cognitive networking paradigm to the problem of dynamic channel selection in infrastructured wireless networks. We first discuss some of the key challenges associated with the cognitive control of wireless networks. Then we introduce our solution, in which a Neural Network-based cognitive engine learns how environmental measurements and the status of the network affect the performance experienced on different channels, and can therefore dynamically select the channel which is expected to yield the best performance for the mobile users. We carry out performance evaluation of the proposed system by experimental measurements on a testbed implementation; the obtained results show that the proposed cognitive engine is effective in achieving performance enhancements with respect to state-of-the-art channel selection strategies.

Traffic sensing and characterization is an important building block of cognitive networking systems; however, it is very challenging in multi-channel multi-radio wireless networks. The contributions of this paper include the following: (i) a discussion of packet sampling for traffic sensing in multi-channel wireless networks, (ii) a comparison of various time-based sampling strategies using the Kullback-Leibler Divergence (KLD) measure, (iii) a study of the effect of the sampling parameters on the accuracy of the sampling strategies, (iv) the proposal of a new metric (Traffic Intensity) which estimates the busyness of channels by taking into consideration not only the successfully received packets but also corrupt or broken packets, and (v) some preliminary results on the characterization of a campus 802.11 network environment in a spatio-temporal fashion.

In this paper, we argue that network performance can be improved when nodes explicitly exchange protocol information with each other. We present a vision of network society for next generation wireless networks that entails such social networking. We begin by describing our cognitive social network (CosNet) system architecture that enables network nodes to effectively gather, analyze, compact, repositorize, and exchange network experience information. We also describe a host of technical issues that need to be addressed for successful realization of a network society, including the management of control overhead, protecting user privacy, vulnerability to selfish and malicious attacks, and scalability concerns. We demonstrate the utility of our approach by studying CosNet inspired modifications of the IEEE 802.11 MAC algorithm that we call CosMAC, respectively. Simulation results show that CosMAC outperforms the throughput of 802.11 MAC in single-hop wireless LAN scenarios. CosMAC also appears to result in a fairer allocation, recorded by 10-15% improvement in Jain's fairness index.

In this paper, throughput performance of WMNs is studied. In our model, a regular grid backbone network overlays on a random ad hoc network. We propose a framework to calculate non-asymptotic throughput, which can be obtained by computing several deterministic parameters. Two problems are investigated. In Maximum Throughput Partition (MTP) problem, the ideal throughput is achieved by optimally partitioning the network with a proper number of backbone nodes. In Maximum Throughput Partition with Hops' number Constraint (MTPHC) problem, a similar problem is studied but with constraint on the average number of hops in the backbone network. The results show that it is critical to find an appropriate size of the backbone network for a WMN, especially when the hops' number constraint is imposed Our solution of MTPHC problem can be also used to obtain the ideal transmission range when less-than-optimal number of backbone nodes is deployed. Comparing with the minimum transmission range, the ideal one can achieve the same optimal throughput but effectively reduce the average number of hops in mesh backbone communications.

In this paper, we propose a novel asynchronous media access control (MAC) protocol, opportunistic MAC (OMAC), for multiple input multiple output (MIMO) ad-hoc networks. The proposed solution is based on closed loop minimal feedback antenna selection diversity scheme and optimum receive combining. The use of antenna selection diversity contributes to a reduction in the feedback information and the effective interference produced. To utilize the spatial degrees of freedom offered by MIMO, we propose the use of a novel rank based metric to obtain interference information as well as to enable multiple simultaneous transmissions and to make MAC decisions. The rank of the interference matrix, (RI) is used as a metric. We present the performance of the proposed solution from the throughput perspective for a single hop ad-hoc wireless network. Through analysis and simulation, we found that the proposed protocol significantly outperforms 802.11 MIMO and it obtained as high spatial degree of freedom utilization as 85%.

Wireless network characterization is an important task in next generation wireless networks. In order to achieve efficient wireless network characterization, accurate sampling strategies are required. The relative performance of different sampling strategies for assessing various wireless network traffic metrics is significant due to the complexity and expense involved in the collection, storage, and analysis of all the traffic generated in the wireless medium. Since the spectrum used for most wireless networks, especially those based on IEEE 802.11 standards, is divided into several channels, the existing count-based sampling methods demand continuous capture on each channel for selecting the desired packets of interest. Continuous capturing makes the cost of monitoring infrastructure very expensive and hence count-based sampling methods are not scalable. However, the time-based sampling methods which were considered inaccurate in wired network characterization, appear to offer a cost-effective and scalable solution by reducing the cost of resources necessary to accurately characterize the wireless medium. For example, the use of time-based sampling enable us to make use of a single wireless interface for accurately sampling multiple channels. However, in order to achieve this, we need to identify the right set of parameters for time-based sampling. This paper presents a study of the performance of various time-based sampling methods in answering questions related to their use in wireless network traffic characterization. We simulate time-based sampling traces at a variety of granularities using a complete packet trace (i.e., parent population) captured in a campus wireless network environment that aggregates traffic from a large number of nodes. From our analysis using Chi-square test, we found that the timer-driven time-based sampling is more accurate than count-driven time-based sampling for both systematic and stratified sampling schemes.

Cognitive radio networking research today mainly focuses on finding efficient ways to let secondary users access radio spectrum that is licensed to primary users, with minimal interference to the license owners. Physical layer cognition, though very important, is complex, expensive, and can provide only limited information about the higher layer traffic. We argue that, even in the absence of physical layer cognitive capability, higher layer traffic information can still be used to generate sufficient cognitive networking information to improve system performance. In this paper, we present an architecture for cognitive networking and an early prototype and experimental setup of a cognitive network access point (CogNet AP), and we describe our observations and lessons learned from this experimental activity. The CogNet AP gathers, processes, analyzes, and stores information available through its monitoring interface in order to build a cognitive local repository which holds the spatio-temporally tagged network traffic information. The inexpensiveness of the components used for building the CogNet AP shows the flexibility of building Cognitive Network elements compared to cognitive radio devices. The proposed cognitive networking architecture and prototype point to the many possible application scenarios and research potential for such systems which use temporal patterns of higher layer traffic information. From our experiments we found that the use of cognitive information derived from higher networking layers resulted in achieving better system throughput.

Though the popular IEEE 802.11 DCF is designed primarily for wireless LAN (WLAN) environments, today it is being widely used for wide area wireless mesh networking. The protocol parameters of IEEE 802.11 such as timeout values, interframe spaces, and slot durations, which are sufficient for a general WLAN environment need to be modified in order to efficiently operate in wide area wireless mesh networks. The current wide area wireless mesh network deployments use manual configuration of these parameters to the upper limit which essentially makes the networks operate at lower system efficiency. In this paper, we propose d802.11 (dynamic 802.11) which dynamically adapts the protocol parameters in order to operate at varying link distances. We present three strategies, (i) multiplicative timer back-off (MTB), (ii) additive timer back-off (ATB), and (iii) link RTT memorization (LRM), to adapt theACK_TIMEOUTin d802.11 in order to provide better adaptation for varying link dimensions. Through extensive simulation experiments we observed significant performance improvement for the proposed strategies. We also theoretically modeled the maximum throughput as a function of the link dimension for the proposed system. Our results show that the LRM technique provides the best adaptation compared to all other schemes.

Wireless mesh networks (WMNs) are formed by self-organized wireless nodes that use multi-hop wireless relaying. These networks are useable in a variety of situations ranging from fixed residential broadband networking based on rooftop wireless mesh nodes to emergency response networks for handling large scale disasters. Quick deployability, minimal configuration, broadband communication, and easiness of reconfigurability are the major characteristics that make WMNs a suitable choice for emergency applications. There exist several open research issues in using such WMNs for emergency response applications. One example is the deployment strategy which must be in accordance with the principal application and its topological requirements. We, in this paper, present a hybrid distributed wireless networking architecture, extreme networking system (ENS), and present large set of performance observations collected from a real distributed hybrid wireless mesh network used for supporting a medical emergency response application. We present the traffic behavior observed in our network when a client server medical emergency response application is employed. The performance observations on real-traffic scenarios for emergency response application underlines the need for focusing further research on topology control, reliability, service availability, and distributed management.

The use of Wireless in Local Loop (WiLL) has generated considerable interest due to the advantages it offers such as ease and low cost of deployment and maintenance. With an increase in the number of subscribers in the network, it becomes expedient to employ spectrum reusability techniques such as the use of multihop relaying in order to improve the capacity of the wireless systems. Throughput enhanced Wireless in Local Loop (TWiLL) is one such architecture that employs multihop relaying and shortcut relaying to reuse bandwidth in WiLL Systems. Compared to other multihop wireless network architectures, TWiLL architecture assumes significance due to its potential use in fixed wireless broadband services such as LMDS (Local Multipoint Distribution Service) and MMDS (Multichannel Multipoint Distribution System). Analysis of the Call Acceptance Ratio (CAR) in multihop wireless architectures including TWiLL is nontrivial as the Erlang B formula no longer holds. In this paper, we build multidimensional Markov Chains to analyze the performance of multihop wireless systems such as TWiLL that has multiple types of channels. We also compare the results of our analysis with results from simulations. We observe that multihop relaying and shortcut relaying lead to a significant increase in the CAR of WiLL systems. Also, the free space propagation model that is normally used to model the radio channel is a very unrealistic model and does not consider reflection, diffraction, scattering, and multipath propagation that hinder transmissions in WiLL systems. In this paper, we studied the effect of several realistic radio channel propagation models on the performance of the TWiLL system through analysis and simulations.

The use of traditional TCP, in its present form, for reliable transport over ad hoc wireless networks (AWNs) leads to significant degradation in the network performance, in terms of reduction in average network throughput and increase in packet losses. This is primarily due to the congestion window updation and congestion control mechanisms employed by TCP. TCP follows a deterministic approach for updating the size of the congestion window, which is less suitable for loss-prone AWNs as it leads to very frequent occurrences of congestion in the network. Another reason is TCP invokes the congestion control mechanism for both congestion and wireless losses, as it cannot distinguish between them. Hence, in order to use TCP in AWNs, an efficient mechanism must be provided with TCP for updating the size of the congestion window based on the network conditions and distinguishing the congestion losses from wireless losses. In order to address these problems, we propose Learning TCP, a novel learning automata based reliable transport protocol for AWNs, which efficiently adjusts the size of the congestion window and thus reduces the packet losses. The key idea behind Learning-TCP is that, it dynamically adapts to the changing network conditions by observing the occurrence of events, such as arrival of acknowledgment (ACK) and duplicate ACK (DUPACK) packets and appropriately updates the congestion window size. In addition to this, we use a deterministic approach for packet loss discrimination, in order to take the appropriate action for each type of loss. Learning-TCP, unlike other existing proposals for reliable transport over AWNs, does not require any explicit feedback, such as congestion, link failure, and available bandwidth notifications, from the network. We provide extensive simulation studies of Learning-TCP under varying network conditions that show increased throughput and reduced packet loss compared to that of the traditional TCP.

The issue of providing Quality of Service (QoS) guarantees in an Ad~hoc wireless network is a very challenging problem. In this paper, we make the following contributions: (i) analytically derive bounds for the end-to-end call acceptance rate using existing queueing theory methods, (ii) study the impact of the routing scheme on the end-to-end call acceptance rate, and (iii) propose a differentiated services scheme for deterministically providing QoS guarantees.Unlike existing studies which analyze the transport capacity, we focus on the end-to-end call acceptance. The framework that we assume is that of a TDMA-based Ad~hoc wireless network. The routing scheme employed influences the end-to-end call acceptance of the network. The metrics that we consider are the call acceptance probability and the system saturation probability (i.e., the probability that the network is in a state in which every new call is rejected). We derive general bounds on the call acceptance and the system saturation for the case of differentiated-classes of users in the network. These bounds indicate the number of calls of the highest priority class that can be admitted into the network.Simulation studies were carried out to study the effect of load, hopcount, and the influence of the routing protocol on the call acceptance. The increase in the call acceptance rate with the introduction of load-balancing highlights the importance of load-balancing in enhancing the system performance. From these studies, we arrive at the following results: (i) load-balancing leads to significant improvement in the end-to-end call acceptance rate, and is an important factor in attaining the maximum end-to-end call acceptance rate in a given network and (ii) it is indeed possible to provide deterministic QoS guarantees for a designated set of nodes which are characterized by "deterministic guarantee limit".

In wireless sensor networks, efficient usage of energy helps in improving the network lifetime. As the battery of a sensor node, in most cases, cannot be recharged or replaced after the deployment of the sensors, energy management becomes a critical issue in such networks. In order to detect an event, a sensor network spends majority of the time in monitoring its environment, during which a significant amount of energy can be saved by placing the radio in the low-power sleep mode. This can be achieved by using a dual frequency radio setup. However, such energy saving protocols increase the latency encountered in setting up a multihop path. We, in this paper, propose a reservation scheme, latency minimized energy efficient MAC protocol (LEEM), which is a novel hop-ahead reservation scheme in a dual frequency radio to minimize the latency in the multihop path data transmission by reserving the next hop's channel a priori. Thus, in a multihop sensor network, a packet can be forwarded to the next hop, as soon as it is received by a sensor node, which helps in eliminating the delay incurred for setting up the path. Simulation results show that LEEM consumes lesser power and reduces end-to-end latency by around 50% than that of the existing schemes

Sensor networks consist of small wireless sensor nodes deployed randomly over an area to monitor the environment or detect intrusion. The coverage provided by sensor networks is very crucial to their effectiveness. Many of the important applications of sensor networks demand autonomous mobility for the sensor nodes. Early failure of sensor nodes can lead to coverage loss that requires coverage maintenance schemes. In this paper, we propose Dynamic Coverage Maintenance (DCM) schemes that exploit the limited mobility of the sensor nodes. The main objective of coverage maintenance is to compensate the loss of coverage with minimum expenditure of energy. We propose a set of DCM schemes which can be executed on individual sensor nodes having a knowledge of only their local neighborhood topology. We propose four algorithms to decide which neighbors to migrate, and to what distance, such that the energy expended is minimized and the coverage obtained for a given number of live nodes is maximized. The decision and movement is completely autonomous in the network, and involves movement of one-hop neighbors of a dead sensor node. We also propose an extension to these algorithms, called Cascaded DCM, which extends the migrations to multiple hops. We have also compared the performance of the different algorithms in terms of the improvement in coverage, average migration distance of the nodes, and the lifetime of the network.

Supporting real-time traffic in ad hoc wireless networks is considered as a challenging problem. Existing bandwidth reservation mechanisms assume a TDMA environment where achieving time synchronisation is expensive in terms of resources. Heuristics that exist for slot allocation schemes assume a CDMA over TDMA model in order to alleviate the presence of hidden terminals. Slot allocation strategies in the presence of hidden terminals assume significance in a single channel system for supporting delay sensitive traffic. In this paper, we propose three heuristics for the slot allocation process in asynchronou single channel multihop wireless networks in the presence of hidden terminals. The heuristics we propose are the early fit reservation (EFR), minimum bandwidth-based reservation (MBR) and position-based hybrid reservation (PHR). The EFR heuristic assigns bandwidth link-by-link in the forward path. The MBR heuristic allocates bandwidth to the links in the increasing order of free conn-slots. The PHR heuristic assigns bandwidth for every link proportional to its position in the path. Simulation studies show that EFR performs better in terms of delay characteristics. MBR provides better call blocking performance at the cost of high end-to-end delay. PHR provides a better delay performance compared to MBR and better call blocking performance comparedto EFR. Copyright © 2004 John Wiley & Sons, Ltd.

In this paper, we address the issue of providing multimedia traffic support in asynchronous ad hoc wireless networks. Since multimedia traffic has stringent bounds on end-to-end delay, we present a resource reservation for transmitting in such traffic. The existing asynchronous MAC protocols such as RTMAC (B.S. and C. Siva Ram Murthy, August 2002) and MACA/PR (C.R. Lin and M. Gerla, March 1999) when used for multimedia traffic provide inefficient utilization of network resources and affect call acceptance ratio and call drop ratio of multimedia traffic severely. Hence in this work, we modify the RTMAC protocol for supporting multimedia traffic so that it overcomes these limitations and improves packet delivery ratio and end-to-end delay of such traffic. The core concept of this protocol is a novel slot allocation strategy for efficient utilization of the available bandwidth for carrying multimedia traffic and best-effort traffic. Extensive simulations were performed to assess the performance of the protocol under varying network conditions. The simulations clearly indicate the gains in using such a slot allocation strategy for carrying multimedia traffic.

A major issue in the energy-constrained ad hoc wireless networks is to find ways that increase their lifetime. The communication protocols for these networks have to be designed such that they are aware of the state of the batteries. In this paper, we propose a novel battery aware medium access control (BAMAC(k)) protocol that takes benefit of the chemical properties of the batteries and provides a longer life for the mobile nodes' battery. The proposed protocol extends the battery lifetime and consumes lesser percentage nominal capacity of the battery per packet transmission compared to the IEEE 802.11 and the DWOP (distributed wireless ordering protocol), respectively. A discrete chain Markov model is used to theoretically analyze the protocol, the correctness of which is verified through a detailed simulation study. The performance results show that BAMAC(k) outperforms IEEE 802.11 and DWOP MAC protocols, in terms of power consumption, fairness, and lifetime of the nodes.

The issue of providing QoS guarantees in an ad hoc wireless network is a challenging problem. Irrespective of the nature of the routing and reservation protocol used in the QoS scheme, there is an inherent limitation on the kind of QoS guarantees that can be provided. Unlike existing studies which analyze the transport capacity, we focus on the achievable capacity. The framework that we assume is that of a TDMA-based network. In this paper, we investigate the achievable capacity and the influence of routing protocols on it. The metrics that we consider are the call acceptance probability and the system saturation probability. We derive general bounds for the case of multiple-classes of users in the network. These bounds indicate the number of calls of the highest priority class that can be admitted into the network. Simulation studies were performed to study the effect of load, hopcount, and the routing protocol on the call acceptance. The increase of the call acceptance with the introduction of load-balancing highlights the importance of load-balancing in enhancing the system performance.

One of the challenging issues in the energy-constrained ad~hoc wireless networks is to find ways that increase their lifetime. Squeezing maximum energy from the battery of the nodes of these networks requires the communication protocols to be designed such that they are aware of the state of the batteries. Traditional MAC protocols for ad~hoc networks are designed without considering the battery state. Major contributions of this paper are: (a) a novel distributed Battery Aware Medium Access Control (BAMAC(k)) protocol that takes benefit of the chemical properties of the batteries, to provide fair scheduling and increased network and node lifetime through uniform discharge of batteries, (b) a discrete time Markov chain analysis for batteries of the nodes of ad~hoc wireless networks, and (c) a thorough comparative study of our protocol with IEEE 802.11 and DWOP (Distributed Wireless Ordering Protocol) MAC protocols. The key idea proposed in this paper is to piggy-back nodes' battery-state information with the packets sent by the nodes by means of which the nodes are scheduled to ensure a uniform battery discharge. We model the operation of the battery using a discrete time Markovian chain. Using the theoretical analysis, we calculate lifetime of the battery in terms of maximum number of packets that a node can transmit before its battery drains fully. Extensive simulations have shown that our protocol extends the battery lifetime consuming 96% and 60% less percentage nominal capacity spent per packet transmission compared to the IEEE 802.11 and the DWOP MAC protocols, respectively. In general, performance results show that BAMAC(k) outperforms IEEE 802.11 and DWOP MAC protocols, in terms of power consumption, fairness, and lifetime of the nodes. We have also analyzed the factors that influence the uniform discharge of batteries and their lifetime.

One of the challenging issues in the energy-constrained ad hoc wireless networks is to find ways that increase their lifetime. Squeezing maximum energy from the battery of the nodes of these networks requires, the communication protocols to be designed such that they are aware of the state of the batteries. Traditional ad hoc wireless MAC protocols are designed without considering the battery state. We propose a novel battery aware medium access control (BAMAC) protocol that takes benefit of the chemical properties of the batteries to provide the longest life for the mobile nodes' battery. The proposed protocol extends the battery lifetime consuming 70% and 21% less percentage nominal capacity of the battery per packet transmission compared to the IEEE 802.11 and the DWOP (distributed wireless ordering protocol) respectively. A discrete chain Markov model is used to theoretically analyze the battery behavior. We have provided a detailed simulation study on the performance and the results show that BAMAC outperforms DWOP and IE EE 802.11 MAC protocols, in terms of power consumption, fairness, and lifetime of the nodes.

The rapid emergence of Wi-Fi hotspots (access points), that are aimed at providing broadband wireless access to users in and around places of commercial interest, presents the unique problem of integrating existing cellular networks with these. We present a novel architecture that explores the interoperability issues between Wi-Fi hotspots and packet cellular networks. In the presence of multiple wireless networks with different access costs, different areas of coverage and bandwidth, the user's choice to select a particular network can significantly impact user benefits and resource usage. We identify three major user profiles - bandwidth conscious, cost conscious and glitch conscious - and study their impact on resource utilization. Contrary to intuition, simulation experiments have shown that bandwidth conscious users may get fewer bandwidth resources compared to glitch conscious users at high mobility. Similarly, it was found that bandwidth conscious users achieve high packet delivery ratios, even while incurring lower costs than cost conscious users, in certain situations. Although increasing the number of access points (APs) leads to higher packet delivery ratios, system performance degrades when the number of APs becomes very large.

The use of wireless in local loop (WiLL) has generated considerable interest due to the advantages it offers such as ease and low cost of deployment and maintenance. Directional multihop wireless in local loop (DWiLL), a new architecture proposed in this paper, employs a unique combination of directional multihop relaying in the uplink and single hop relaying in the downlink to reuse bandwidth and thus improve the throughput of WiLL systems. Analysis of the call acceptance ratio (CAR) in a DWiLL system is non-trivial as the Erlang B formula no longer holds. In This work we build multi-dimensional Markov chains to analyze the performance of the DWiLL system. We observe that directional multihop relaying leads to a significant improvement in throughput of WiLL systems.

Ad hoc wireless networks have been an increasingly important area of research in the recent past. One issue of great interest in this area is the provision of real-time support. While existing military applications use reservation-based approaches to provide real-time bandwidth guarantees, these schemes are adversely affected by node mobility. We propose an enhanced real-time support scheme that uses a novel out-of-band signaling mechanism to predict future mobility patterns and take corrective action when needed. We also propose an architecture to support differentiated service classes. This helps mobility affected nodes to take proactive measures so as to offer better real-time services to bandwidth critical applications. Through extensive simulations, we show that the use of the out-of-band signaling leads to better real-time support overall, and better response to the more critical classes as needed. We also provide a theoretical analysis for estimating the probability of disruption of a real-time call.

Interplanetary ad hoc networks (IPANs) aim to establish a communication infrastructure in deep space, connecting planets, natural and artificial satellites, and mission elements. The communication links in IPANs have low bandwidth, high error rate, and high latency. The connectivity of the network is intermittent, affected by movement of planets out of range of each other and occlusion of a planet by another. Also, the satellites and mission stations are power constrained, which makes traditional routing protocols extremely expensive in terms of time and energy consumed. However, the determinism in the orbital patterns of planets and satellites enables predictive route-building and repair. The main contributions of this paper are (i) identification of the issues involved in routing over IPANs, (ii) graph-theoretic modeling of the interplanetary backbone network, and (iii) proposal of a routing protocol, MARVIN, for interplanetary backbone networks. The proposed routing protocol, MARVIN, for movement-aware routing over interplanetary networks, makes novel use of the determinism in planetary movements. MARVIN uses the ephemeris table data for planets to precisely determine the location of planets at any instant of time, and reconfigures routes a priori, in anticipation of link-breaks. This eliminates the need for expensive topology discovery and distribution of topology information. We have simulated MARVIN over the IPAN consisting of the nine planets and the moon. It can build the routing table for any period of time given the ephemeris data tables. The graph-theoretic approach also helps in defining the stability of links of the IPAN, and can be used to choose relatively long-lasting links to reduce the number of route reconfigurations. MARVIN is studied for a variety of routing metrics such as shortest path, minimum power, and minimum end-to-end delay, and sample routing tables have been presented.

Wireless networks are inherently limited by the bandwidth constraint. MAC protocols for wireless local area networks (WLANs) play the important role of arbitrating and statistically multiplexing the transmission requests of various stations contending to access the channel. The performance of IEEE 802.11 degrades in ad hoc networks because of the presence of hidden and exposed terminals. To counter these problems, we propose a new MAC protocol called interleaved carrier sense multiple access (ICSMA) protocol for ad hoc wireless network. The performance of ICSMA was compared with single channel 802.11 MAC protocol and with 802.11 MAC protocol over two channels with half the bandwidth through extensive simulation studies. Results show that ICSMA performs better with respect to throughput, access delay, throughput fairness, and delay fairness when compared with IEEE 802.11.

Multihop cellular networks (MCNs) have been proposed as a throughput enhancement alternative for traditional cellular networks. In MCNs, as opposed to traditional cellular networks, both the base station (BS) and the mobile stations (MSs) play a significant role in forwarding data. In this paper, we propose an efficient routing protocol for single interface MCNs and compare it with an existing routing protocol. The primary motivation for exploring this single interface mechanism is to provide low cost and low power consumption mobile devices. Since pricing in packet-based data traffic for MCNs is a key issue which is not addressed so far, we proposed a set of incentive-based pricing schemes for packet based traffic that are not bound by mobility or load constraints. We also suggest reimbursement based schemes that take into account the retransmission attempts made by the intermediate nodes. We compare our routing protocol single interface MCN routing protocol (SMRP) with base driven multihop bridging protocol (BMBP) and study a set of incentive-based pricing schemes for data traffic in MCNs using extensive simulation using GloMoSim.

Existing multicast routing protocols for mobile ad hoc networks can be broadly classified into two categories, tree based protocols and mesh based protocols. Mesh based protocols have high packet delivery ratio compared to tree based protocols, but incur more control overhead. The packet delivery ratio of tree based protocols decreases with increasing mobility. This is due to the occurrence of frequent tree breaks and lack of proper tree maintenance mechanisms. These tree breaks result in frequent flooding of JoinQuery packets by the multicast group member nodes which try to get re-connected to the tree. These broadcast packets collide with the data packets and reduce the efficiency of the protocol. We propose an efficient protocol which we call as preferred link based multicast protocol (PLBM). PLBM uses a preferred link approach for forwarding JoinQuery packets. Subsets of neighbors of a node are selected using a preferred link based algorithm. These nodes, termed as preferred nodes, are only eligible for further forwarding of JoinQuery packets. We also propose a quick link break detection mechanism that locally repairs broken links. Simulation results show that our protocol performs better than other existing multicast protocols in terms of packet delivery ratio and control overhead.

Ad hoc wireless networks are self-organizing, dynamic topology networks formed by a collection of mobile nodes through radio links. Minimal configuration, absence of infrastructure and quick deployment make them convenient for emergency situations apart from military applications. Multicasting plays a crucial role in the application of ad hoc networks. Since bandwidth is limited in ad hoc wireless networks, a multicast routing protocol must be efficient. It is well known that tree based multicast routing protocols are efficient. But, the main drawback of these protocols is that they are not robust enough to achieve high packet delivery ratios. We propose a tree based multicast protocol in which, to make the protocol robust as well as efficient, a node joins the multicast tree by taking into consideration not only the number of forwarding nodes but also the distance between the source and receiver. For tree maintenance, we have used a localized prediction scheme which results in a high packet delivery ratio.

Traditionally, voice communication over the local loop has been provided by wired systems. However there has been an increased interest in the use of radio access technologies in local loops. Such systems which are now popular for their ease and low cost of installation and maintenance are called wireless in local loop (WLL) systems. Subscribers' demands for greater capacity have grown over the years especially with the advent of the Internet. Unlike WLL, wired local loops have responded to these increasing demands through the use of digital technologies such as ISDN and xDSL. Multihop communication has already been studied extensively in ad hoc network environments and has begun making forays into cellular systems as well. Multi-hop communication has been proven as one of the best ways to enhance throughput in a wireless network. We study the issues involved in multi-hop communication in a wireless local loop system and propose a novel WLL architecture called Throughput enhanced Wireless in Local Loop (TWiLL). Through a realistic simulation model we show the tremendous performance improvement achieved by TWiLL over WLL. We also propose pricing schemes which could be applied in such a multi-hop environment.

Ad hoc wireless networks are self-organizing dynamic topology networks formed by a collection of mobile nodes through radio links. Minimal configuration absence of infrastructure and quick deployment make them convenient for emergency situations other than military applications. Multicasting plays a very crucial role in the application of Ad hoc networks. As the number of participants increases scalability of the multicast protocol becomes an important issue. Among the existing multicast protocols On Demand Multicast Routing Protocol (ODMRP) perfo exhibits a high packet delivery ratio even at high mobility. But ODMRP suffers from higher control overhead as the network size and the number of sources increase.In this paper we propose an efficient multicast routing protocol for Ad hoc wireless networks. This protocol reduces the control overhead by dynamically classifying the sources into Active and Passive categories. The control overhead is significantly reduced by about 30% compared to ODMRP which contributes to the scalability of the protocol. We study the effectiveness of the proposed multicast routing protocol by simulation studies and the results show that the multicast efficiency is increased by 10--15% and packet delivery ratio is also improved at high network load.

Multi-hop cellular network (MCN) is an architecture proposed by Lin and Hsu (see INFOCOM 2000. IEEE, 2000) for wireless communication & MCNs combine the benefits of having a fixed infrastructure of base stations and the flexibility of ad-hoc networks. They are capable of achieving much higher throughput than current cellular systems, which can be classified as single-hop cellular networks (SCNs). This work concentrates on MCNs and SCNs using the IEEE 802.11 standard for wireless LANs. We provide a general overview of the architecture and the issues involved in the design of MCNs, in particular the challenges to be met in the design of a routing protocol. We extend the work of Lin and Hsu to enhance the throughput of such networks further. We propose a routing protocol for use in such networks. We conduct extensive experimental studies on the performance of MCNs and SCNs under various load conditions (both TCP and UDP). Then studies clearly indicate that MCNs with the proposed routing protocol are a viable alternative for SCNs, in fact they provide much higher throughput.

We have considered the problem of providing greater throughput in packet data cellular networks. We suggest a novel cellular architecture, the multi-power architecture for cellular networks (MuPAC), based on multiple data channels used at different transmission powers. We discuss path selection mechanism in the context of multi-channel systems and MuPAC. We also offer solutions to problems faced in multi-hop networks: performance degradation at high mobility, pricing issues, partitions etc. MuPAC provides increased throughput compared to existing schemes like the current day cellular systems which can be classified as single-hop cellular network (SCN), and the multi-hop cellular network (MCN). We show using extensive simulations, that MuPAC performs well over a range of node densities, under high mobility, and under high leod conditions. MuPAC can also evolve from the existing infrastructure and offers advantages to both the service provider and the users.

Due to the highly dynamic topology and absence of any fixed infrastructure, stability of selected path is of prime importance in ad hoc networks. The frequent route failure and high control overhead in routing protocols lead to degraded system performance. This paper proposes a stability based distributed adaptive routing protocol for ad hoc networks, which uses the worst case lifetime of wireless links, which is obtained by linear regression of the variation of distance between nodes as the routing metric. An efficient beaconing mechanism, load balancing, pro-active and reactive route reconfiguration mechanisms are also studied with the protocol. The protocol is supported with simulation using GloMoSim.