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Low-Power and Lossy Networks (LLNs) aim at integrating smart objects into the Internet of Things. ieee 802.15.4-TSCH is currently a promising standard for the link layer: it schedules the transmissions and implements slow channel hopping to improve the reliability while the routing layer focuses on constructing distributed routes for a small collection of destinations (i.e. convergecast). We propose here an efficient scheduling policy to exploit an opportunistic feature of the MAC layer: a single transmission is received by a collection of next hops which decide opportunistically which one will forward the packet. We consider here the problem of the optimal scheduling policy for reliability and energy efficiency when considering such opportunistic forwarding at the MAC and routing layers. The simulation results demonstrate the effectiveness of the proposed policy: by effectively selecting the set of parents (i.e. next hops) and carefully considering the channel quality, the energy consumption per packet is reduced. Besides, we also improve the reliability: the network can also use unreliable radio links, where only one of the next hops receives the packet to forward. This scheduling policy may typically be implemented in the PCE of ieee 802.15.4e-TSCH.

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective.

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