Machine to Machine (M2M) communication has gained much momentum in the recent past, both within academia and across different industries. Many of the M2M applications are required to send data to the M2M server connected directly or indirectly to the communication network such as 3GPP network. This requires connecting millions of M2M devices, apart from usual mobile devices, to the 3GPP network. However, this imposes a major deployment and management challenge, since the network was originally not designed to support billions of simultaneous connections. This paper discusses a practical M2M network deployment scenario and the architectural details. The paper provides a novel method to efficiently and effectively maintain and monitor multiplicity of M2M devices deployed for various applications such as monitoring, surveillance and tracking. Simulation result shows the benefits and practical uses of the proposed method.
In a tree-structured ZigBee wireless sensor network, nodes close to the root of the tree (i.e., hot-spot nodes) may exhaust their power earlier than those distant from the root due to heavy loads on packet forwarding. This hot-spot problem is inherent in tree-structured networks and may demand extra energy to recover from failures of hot-spot nodes. In this paper, the backbone-aware topology formation (BATF) scheme is proposed to alleviate the hot-spot problem. BATF utilizes power-rich nodes to form a backbone tree that does not suffer from the hot-spot problem. Each power-rich node independently initiates a ZigBee tree network that attracts associations from ZigBee-compliant devices in order to distribute packet-forwarding loads over a larger set of nodes. Issues of BATF such as the partition of address space and ZigBee-compliant routing are discussed in detail. Simulation results confirm that BATF does alleviate the hot-spot problem as it improves network lifetime as well as data collection capability. Comparisons with native ZigBee protocols show that the improvement comes from our protocol design rather than simply introducing power-rich nodes.
In this paper, we present an architecture for transparent service continuity for cloud-enabled WiFi networks called ARNAB: ARchitecture for traNsparent service continuity viA douBle-tier migration. The term arnab means rabbit in Arabic. It is dubbed for the proposed service architecture because a mobileuser service with ARNAB behaves like a rabbit hopping through the WiFi infrastructure. To deliver continuous services, deploying edge clouds is not sufficient. Users may travel far from the initial serving edge and also perform multiple WiFi handoffs during mobility. To solve this, ARNAB employs a double-tier migration scheme. One migration tier is for user connectivity, and the other one is for edge applications. Our experimental results show that ARNAB can not only enable continuous service delivery but also outperform the existing work in the area of container live migration across edge clouds.
SUMMARYCo-channel interference seriously influences the throughput of a wireless mesh network. This study proposes an end-to-end channel allocation scheme (EECAS) that extends the radio-frequency-slot method to minimize co-channel interference. The EECAS first separates the transmission and reception of packets into two channels. This scheme can then classify the state of each radio-frequency-slot as transmitting, receiving, interfered, free, or parity. A node that initiates a communication session with a quality of service requirement can propagate a channel allocation request along the communication path to the destination. By checking the channel state, the EECAS can determine feasible radio-frequency-slot allocations for the end-to-end path. The simulation results in this study demonstrate that the proposed approach performs well in intra-mesh and inter-mesh communications, and it outperforms previous channel allocation schemes in end-to-end throughput.
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