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A backpressure-based data collecting scheme has been applied in the Internet of Things, which can control the network congestion effectively and increase the network throughput. However, there is an obvious shortcoming in the traditional backpressure data collecting scheme for the network service chain. It attempts to search all possible paths between source node and destination node in the networks, causing an unnecessary long path for data collection, which results in large end-toend delay and redundant energy consumption. To address this shortcoming of backpressure data collecting scheme in the Internet of Things, this article proposes an energy-aware and distance-aware data collecting scheme to enhance the lifetime of backpressure-based data collecting schemes. We propose an energy- and distance-based model that combines the factors of queue backlog, hop counts, and residual energy for making routing decisions. It not only reduces the unnecessary energy consumption, but also balances the residual energy. The experiment results show that the proposed scheme can reduce unnecessary energy consumption and end-to-end delay compared to the traditional and LIFO-based schemes. Meanwhile, it balances the energy of nodes and extends the lifetime of an Internet of Things. [ABSTRACT FROM PUBLISHER]

Socially aware networking (SAN) is a new communication paradigm, in which the social characteristics of mobile nodes are exploited to improve the performance of data distribution. In SAN, mobile carriers may exhibit selfish behaviors and refuse to relay messages for others for various reasons, such as limited resources (e.g., buffer, energy, and bandwidth) or social relationships. Several incentive schemes have recently been investigated to stimulate selfish users for cooperation in data forwarding. However, a majority of the existing methods have not fully studied nodes' social relationships in their selfish behaviors. In this paper, we propose a copy adjustable incentive scheme (CAIS), which adopts the virtual credit concept to stimulate selfish nodes to cooperate in data forwarding. In CAIS, we consider a network in which the nodes are divided into certain communities based on their social relationships. Then, we apply two types of credits, i.e., social credit and nonsocial credit, to reward the nodes when they relay data for other nodes inside their community or outsiders, respectively. Based on our mechanism, the number of messages a node can replicate to other nodes is adjusted according to its cooperation level and earned credits. To further improve the performance of CAIS, a single-copy data replication policy is employed, which manages the credit distribution of each node according to its available resources. The results of our extensive experiments using both synthetic and trace-driven simulations illustrate that CAIS copes well with node selfishness in community-based networks and outperforms other benchmark protocols with high data delivery ratio, low communication overhead, and short data delivery latency. [ABSTRACT FROM PUBLISHER]