PRK-based scheduling for predictable link reliability in wireless networked sensing and control

In this chapter, a thorough treatment of the modulation schemes for UG Wireless is presented. The effects of soil texture and water content on the capacity of multi-carrier modulation in WUC are discussed. The multi-carrier capacity model results are analyzed. Moreover, the underground MIMO design for underground communications is explained thoroughly. An analysis of medium access in wireless underground is done as well. Furthermore, the soil properties are considered for cross-layer communications of UG wireless. The performance analysis of traditional modulation schemes is also considered. The soil moisture-based modulation approach is also explored in this chapter. The connectivity and diversity reception approaches are discussed for wireless underground communications. The connectivity and interference models are studied for Ad-Hoc and Hybrid Networks. The topology control mechanisms for maintaining network connectivity are explored for maximizing network capacity under the physical models (e.g., the protocol interference model and physical interference model). Moreover, the underground diversity is examined for 3W-Rake receiver and coherent detection along with experimental evaluation and comprehensive analysis of performance of equalization techniques.

Fractional Link scheduling is one of the most fundamental problems in wireless networks. The prevailing approach for shortest fractional link scheduling is based on a reduction to the maximum-weighted independent set problem, which itself may not admit efficient approximation algorithms. In addition, except for the wireless networks under the protocol interference model, none of the existing scheduling algorithms can produce a link schedule with explicit upper bounds on its length in terms of the link demands. As the result, the polynomial approximate capacity regions in these networks remain blank. This paper develops a purely combinatorial paradigm for fractional link scheduling in wireless networks. In addition to the superior efficiency, it is able to provide explicit upper bounds on the lengths of the produced link schedule. By exploiting these upper bounds, polynomial approximate capacity regions are derived. The effectiveness of this new paradigm is demonstrated by its applications in wireless networks under the physical interference model and wireless MIMO networks under the protocol interference model.

Minimum-Latency Aggregation Scheduling (MLAS) is a problem of fundamental importance in wireless sensor networks. There however has been very little effort spent on designing algorithms to achieve sufficiently fast data aggregation under the physical interference model which is a more realistic model than traditional protocol interference model. In particular, a distributed solution to the problem under the physical interference model is challenging because of the need for global-scale information to compute the cumulative interference at any individual node. In this paper, we propose a distributed algorithm that solves the MLAS problem under the physical interference model in networks of arbitrary topology in O(K) time slots, where K is the logarithm of the ratio between the lengths of the longest and shortest links in the network. We also give a centralized algorithm to serve as a benchmark for comparison purposes, which aggregates data from all sources in O(log3n) time slots (where n is the total number of nodes). This is the current best algorithm for the problem in the literature. The distributed algorithm partitions the network into cells according to the value K, thus obviating the need for global information. The centralized algorithm strategically combines our aggregation tree construction algorithm with the non-linear power assignment strategy in [9]. We prove the correctness and efficiency of our algorithms, and conduct empirical studies under realistic settings to validate our analytical results.

The capacity of wireless multi-hop networks has been studied extensively in recent years. Most existing work tackles the problem from an asymptotic perspective and assumes a simplified physical layer model, as e.g., the protocol interference model or the path loss radio propagation. Real life network planning, provisioning and deployment can only be done with more precise statements about capacity in finite networks. With this in mind, we adopt a numerical approach based on Monte-Carlo methods to study capacity under various interference and radio propagation models, including the physical interference model and log-normal shadowing radio propagation. Our results indicate that, depending on the interference model, capacity may experience a three phase transition related to the connectivity of the network. We further show that throughput capacity increases in the presence of randomized radio propagation, even above the critical node density. Our analysis of the numerical data illustrates that log-normal shadowing creates more interference, but decreases the total amount of transmissions to be scheduled.

Beaconing is a primitive communication task in which every node locally broadcasts a packet to all of its neighbors within a fixed distance. The problem Minimum Latency Beaconing Schedule (MLBS) seeks a shortest schedule for beaconing subject to the interference constraint. MLBS has been well studied when all the nodes are always awake. However, it is well-known that the networking nodes often switch between the active state and the sleep state to save energy. A node in duty-cycled scenarios may require transmitting multiple times to inform all of its neighbors due to their different active times. Thus, all of the known algorithms for MLBS are not suitable for duty-cycled multihop wireless networks. In this paper, we study MLBS in Duty-Cycled multihop wireless networks (MLBSDC). We first present two constant-approximation algorithms for MLBSDC under the protocol interference model with the approximation bounds independent of the length of a scheduling period. Then, we develop an efficient algorithm for MLBSDC under the physical interference model. To the best of our knowledge, this is the first paper that develops efficient algorithms for MLBSDC under either of these two interference models.

The emerging energy-harvesting technology enables charging sensor batteries with renewable energy sources, which has been effectively integrated into Wireless Sensor Networks (EH-WSNs). Due to the limited energy-harvesting capacities of tiny sensors, the captured energy remains scarce and differs greatly among nodes, which makes the data aggregation scheduling problem more challenging than that in energy-abundant WSNs. In this article, we investigate the Minimum Latency Aggregation Scheduling (MLAS) problem in EH-WSNs. First, we identify a new kind of collision in EH-WSNs, named as energy-collision, and design several special structures to avoid it during data aggregation. To reduce the latency, we try to choose the parent adaptively according to nodes’ transmission tasks and energy-harvesting ability, under the consideration of collisions avoidance. By considering transmitting time, residual energy, and energy-collision, three scheduling algorithms are proposed under protocol interference model. Under physical interference model, several approximate algorithms are also designed by taking account of the interference from the nodes several hops away. Finally, the theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency.

Beaconing is a primitive communication task in which every node locally broadcasts a packet to all its neighbors within a fixed distance. Assume that all communications proceed in synchronous time-slots and each node can transmit at most one fixed-size packet in each time-slot. The problem Minimum-latency beaconing schedule (MLBS) in multihop wireless networks seeks a shortest schedule for beaconing subject to the interference constraint. MLBS has been intensively studied since the mid-1980s, but all assume the protocol interference model with uniform interference radii. In this paper, we first present a constant-approximation algorithm for MLBS under the protocol interference model with arbitrary interference radii. Then, we develop a constant-approximation algorithm for MLBS under the physical interference model. Both approximation algorithms have efficient implementations in a greedy first-fit manner.

The wireless relay mesh network (WRMN) is designed to provide robust and fault tolerant communications between relay and user nodes in broadband wireless networks. In this paper, we investigate the benefits of decoupled optimization of routing and scheduling in WRMNs using the physical interference model and spatial reuse to maximize overall throughput. We model the routing optimization as a linear program using multicommodity flows (MCF). We refer to this problem as multicommodity flow routing optimization (MCF-ROPT). Using the flow per link determined from MCF-ROPT, we develop an optimization formulation to schedule the link traffic such that interference is minimized and time slots are reused appropriately based on spatial TDMA (STDMA). Furthermore, our scheduling approach incorporates the effect of reuse of multiple carriers on the transmission schedule. We refer to this problem as SM-TSS (STDMA multicarrier traffic sensitive scheduling). The SM-TSS is NP-hard and thus is solved using column generation. We compare our formulations with decoupled optimizations that use the protocol interference model and/or single carrier systems and show that our approach guarantees higher throughput by mitigating interference effectively.

In this paper, a model for the static channel assignment in multi-radio multi-channel wireless mesh networks is proposed. We describe an interference model in wireless communication environment. The degree of detail in the model determines the accuracy of channel assignment. In many wireless mesh networks studies, the simplistic protocol interference model is adopted, but the model is usually not realistic and practical. Therefore, we construct a physical interference model and put forward a pure integer quadratic programming (PIQP) model to solve the channel assignment problem and maximize the capacity of wireless mesh networks. The feasibility and effectivity of the channel assignment solution are suggested by the results of simulation.

In time division multiple access (TDMA)-based wireless mesh networks, interference relationships should be considered when time slots are assigned to links. In graph theory-based time slot assignment algorithms, the protocol interference model is widely used to determine radio interference information, although it is an inaccurate model of actual radio interference. On the other hand, the signal-to-interference-plus-noise-ratio model (SINR model) gives more accurate interference relationships but is difficult to apply to time slot assignment algorithms since the radio interference information cannot be determined before time slot assignment. In this paper, we investigate the effect of the parameters of the protocol interference model on the accuracy of the interference relationships determined using this model. Specifically, after assigning time slots to links based on the protocol interference model with various interference ratios, which is the major parameter of the protocol interference model, we compare the interference relationship among links in the protocol interference and SINR models. Through simulation experiments, we show that accuracy of the protocol interference model is improved by up to 15% by adjusting the interference ratios of the protocol interference model.

Interference-aware scheduling for wireless communications is crucial to improve the network throughput. In this paper, we study the problem of Maximum Weighted Independent Set of Links (MWISL) under the physical interference model in wireless networks. Given a set of communication links distributed in a two-dimensional Euclidean plane, assume each link is associated with a positive weight which represents the benefit of transmitting along the link, the objective is to seek an independent set of links subject to the physical interference constraints with maximum weighted sum. To the best of our knowledge, no algorithm for MWISL under physical interference model has been proposed. We focus on MWISL in the oblivious power assignment setting.

Wireless mesh network (WMN) is emerging as an important networking architecture for future wireless communications. The mesh mode supported in IEEE 802.16 protocol provides a TDMA solution for WMN, in which scheduling is an important issue. In this paper, we discuss the issues on how to satisfy a set of bandwidth requests in IEEE 802.16 WMNs using minimal radio resources (or solving minimal schedule length problem). In consideration of transmission overhead and adaptive modulation and coding (AMC), two cross-layer scheduling algorithms are proposed, namely max-transmission and priority-based algorithms. In particular, they are proposed based on a physical interference model, instead of a protocol interference model as suggested in the literature. For the priority-based algorithm, we study several priority criteria based on different cross-layer information. An iterative scheme for QoS traffic is introduced to guarantee fairness when traffic load exceeds the network capacity. Simulation results show that our algorithms outperform the existing schemes based on protocol model, and they also ensure better fairness among different nodes.

Analysis of mobility impact on interference in cognitive radio networks

As a virtual backbone structure, connected dominating sets (CDSs) play an important role in topology control for wireless networks. In this paper, we develop a distributed self-stabilizing CDS construction algorithm under the SINR model (also known as the physical interference model), a more practical yet more challenging interference model for distributed algorithm design. Specifically, we propose a randomized distributed algorithm that can construct a CDS in O (log n) timeslots with a high probability, where n is the total number of nodes in the network. The constructed CDS achieves constant approximation in both density and diameter. To the best of our knowledge, this is the first known asymptotically optimal self-stabilizing result in terms of both density and diameter for distributed CDS construction under the practical SINR model.

Maximizing quality of aggregation (QoA) is an essential requirement for real-time wireless sensor networks (WSNs) where the participation of all sensor nodes in data aggregation is hampered by the underlying sink deadline and interference constraints. This problem, however, remains unsolved under the physical interference model that captures the reality more accurately than the widely used graph-based models. In this paper, we formulate an optimization problem of maximizing QoA under deadline and interference constraints in commonly seen tree- based WSNs. We prove the problem to be NP- complete, and then propose a suboptimal scheduling algorithm which relies on a Markov approximation framework and modifies the matching graphs in order to handle the globally-imposed interference constraints. The problem and its solution are then coupled with successive interference cancellation (SIC) to improve QoA by increasing the number of concurrent transmissions. Our evaluation has shown the proposed solution to be effective under the physical interference model, both with and without SIC.