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The prominence of Machine-to-Machine (M2M) communications in the future wide area communication networks place various challenges to the cellular technologies such as the Long Term Evolution (LTE) standard, owing to the large number of M2M devices generating small bursts of infrequent data packets with a wide range of delay requirements. The channel structure and Quality of Service (QoS) framework of LTE networks fail to support M2M traffic with multiple burst sizes and QoS requirements while a bottleneck often arises from the limited control resources to communicate future uplink resource allocations to the M2M devices. Moreover, many of the M2M devices are battery-powered and require a low-power consuming wide area technology for wide-spread deployments. To alleviate these issues, in this article we propose an adaptive semi-persistent scheduling (SPS) scheme for the LTE uplink which caters for multi-service M2M traffic classes with variable burst sizes and delay tolerances. Instead of adhering to the rigid LTE QoS framework, the proposed algorithm supports variation of uplink allocation sizes based on queued data length yet does not require control signaling to inform those allocations to the respective devices. Both the eNodeB and the M2M devices can determine the precise uplink resource allocation related parameters based on their mutual knowledge, thus omitting the burden of regular control signaling exchanges. Based on a control parameter, the algorithm can offer different capacities and levels of QoS satisfaction to different traffic classes. We also introduce a pre-emptive feature by which the algorithm can prioritize new traffic with low delay tolerance over ongoing delay-tolerant traffic. We also build a model for incorporating the Discontinuous Reception (DRX) mechanism in synchronization with the adaptive SPS transmissions so that the UE power consumption can be significantly lowered, thereby extending their battery lives. The simulation and performance analysis of the proposed scheme shows significant improvement over the traditional LTE scheduler in terms of QoS satisfaction, channel utilization and low power requirements of multi-service M2M traffic. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid resource management system for the uplink in Universal Mobile Telecommunications System wideband code-division multiple access (WCDMA) with components in the Node-B and user equipment (UE) has been proposed. A rate scheduler in the client focuses on average packet delays as a means of abstracting application-specific requirements from the rest of the resource management scheme. It controls uplink transmission through variable spreading gain to optimize resource usage while meeting target delays. Service change requests from the distributed rate schedulers are collectively processed through interservice and intraservice priority queuing in a manner that is shown to exhibit fairness in allocation of resources when cumulative load exceeds system capacity. The performance of the proposed algorithm is explored through discrete-event simulations for three classes of traffic, namely voice, video, and data, over the WCDMA uplink in the presence of short-term Rayleigh fading, automatic repeat request, forward error correction, target transmission delays to meet the respective quality of service, and frame error rate targets in a 'multicell' environment. The authors analyze two alternatives for distributed resource management with the UE or Node-B in control of rate scheduling and observe the fairness in resource allocation of both systems. Priority of speech, video, and data traffic is respected and reflected in 95th percentile transmission delays for heavily loaded systems. Index Terms--Radio resource management (RRM), rate scheduling, Universal Mobile Telecommunications System (UMTS), uplink, wideband code-division multiple access (WCDMA).

The low‐power short‐range networks have gained prevalence in research fields such as machine‐to‐machine communications and the Internet of things. Given the large number of devices that may exist, the IPv6 over low‐power wireless personal area networks (6LoWPAN) standard is expected to be widely used. Although Contiki, NS‐3, and OMNeT++ have developed the 6LoWPAN model, it is still not available in optimized network engineering tools (OPNET) because it is extremely difficult to interface the built‐in IP module with the customized modules in OPNET. To bridge this gap, we first developed a preliminary 6LoWPAN model and implemented the header compression and header restoration functions to handle the incoming and outgoing packets in OPNET. To further improve the system performance, we also proposed an algorithm that aggregates packets, reduces intranetwork collisions and increases the packet delivery ratio. The model and algorithm in this work are free to download, so researchers from the OPNET community can easily extend this work for their own research in the future. [ABSTRACT FROM AUTHOR]

Wide area wireless systems conventionally employ dynamic scheduling for stochastic or bursty applications and persistent resource allocations of a given period for deterministic applications such as voice. When considering persistent resource allocations for machine-to-machine (M2M) applications from different markets, a wide range of allocation periods may be required to fully support the diversity of applications. The set of periods supported by the wireless system is a compromise between efficient use of the available resources and supporting as many M2M applications as possible. We consider two schemes: a simply periodic system which offers a limited set of periods with very efficient use of resources, and a complex periodic system which offers a wider range of periods at the cost of lower efficiency. We derive formulae for the blocking probability of these two systems by considering different resource sharing policies of the Erlang Multirate Loss Model (EMLM) and the concepts of packing (when a new persistent allocation is admitted to the system) and repacking (when an existing persistent allocation leaves the system). The theoretical models are verified using a discrete event simulation with variable offered traffic loads. The concepts discussed in this paper are generic, but may find particular application in Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) networks for the purposes of system configuration (particularly in terms of the set of periods supported for persistent allocations), resource dimensioning and system performance characterisation. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A variety of scheduling strategies can be employed in wireless systems to satisfy different system objectives and to cater for different traffic types. Static persistent resource allocations can be employed to transfer small M2M data packets efficiently compared to dynamic packet-by-packet scheduling, even when the M2M traffic model is non-deterministic. Recently, adaptive persistent allocations have been proposed in which the volume of allocated resources can change in sympathy with the instantaneous queue size at the M2M device and without expensive signaling on control channels. This increases the efficiency of resource usage at the expense of a (typically small) increased packet delay. In this paper, we derive a statistical model for the device queue size and packet delay in static and adaptive persistent allocations which can be used for any arrival process (i.e., Poisson or otherwise). The primary motivation is to assist with dimensioning of persistent allocations given a set of QoS requirements (such as a prescribed delay budget). We validate the statistical model via comparison with queue size and delay statistics obtained from a discrete event simulation of a persistent allocation system. The validation is performed for both exponential and gamma distributed packet inter-arrivals to demonstrate the model generality. [ABSTRACT FROM PUBLISHER]

With the increasing demand of Machine to Machine (M2M) communications and Internet of Things (IoT) services it is necessary to develop a new network architecture and protocols to support cost effective, distributed computing systems. Generally, M2M and IoT applications serve a large number of intelligent devices, such as sensors and actuators, which are distributed over large geographical areas. To deploy M2M communication and IoT sensor nodes in a cost-effective manner over a large geographical area, it is necessary to develop a new network architecture that is cost effective, as well as energy efficient. This paper presents an IEEE 802.11 and IEEE 802.15.4 standards-based heterogeneous network architecture to support M2M communication services over a wide geographical area. For the proposed heterogeneous network, we developed a new cooperative Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) medium access control (MAC) protocol to transmit packets using a shared channel in the 2.4 GHz ISM band. One of the key problems of the IEEE 802.11/802.15.4 heterogeneous network in a dense networking environment is the coexistence problem in which the two protocols interfere with each other causing performance degradation. This paper introduces a cooperative MAC protocol that utilizes a new signaling technique known as the Blank Burst (BB) to avoid the coexistence problem. The proposed MAC protocol improves the network QoS of M2M area networks. The developed network architecture offers significant energy efficiency, and operational expenditure (OPEX) and capital expenditure (CAPEX) advantages over 3G/4G cellular standards-based wide area networks. [ABSTRACT FROM AUTHOR]

Some M2M applications such as event monitoring involve a group of devices in a vicinity that act in a co-ordinated manner. An LTE network can exploit the correlated traffic characteristics of such devices by proactively assigning resources to devices based upon the activity of neighboring devices in the same group. This can reduce latency compared to waiting for each device in the group to request resources reactively per the standard LTE protocol. In this paper, we specify a new low complexity predictive resource allocation algorithm, known as the one way algorithm, for use with delay sensitive event based M2M applications in the LTE uplink. This algorithm requires minimal incremental processing power and memory resources at the eNodeB, yet can reduce the mean uplink latency below the minimum possible value for a non-predictive resource allocation algorithm. We develop mathematical models for the probability of a prediction, the probability of a successful prediction, the probability of an unsuccessful prediction, resource usage/wastage probabilities, and mean uplink latency. The validity of these models is demonstrated by comparison with the results from a simulation. The models can be used offline by network operators or online in real time by the eNodeB scheduler to optimize performance. [ABSTRACT FROM PUBLISHER]