As one of the three provinces in Northeast China, Liaoning Province is one of the major industrial provinces. With the development of industrialization, the urban environmental pollution in Liaoning Province is becoming more and more serious, which has brought a huge impact on people's daily lives. In order to strengthen the monitoring of urban pollution, this paper proposes a study on the intelligent monitoring platform for urban pollution in Liaoning Province based on big data. This paper combines big data and intelligent monitoring technology to study the intelligent monitoring platform for urban pollution in Liaoning Province based on big data. The monitoring of air pollution in a city in Liaoning Province through simulation experiments verified the reliability of this platform. This paper finds that the average response time of the Liaoning Province's urban pollution intelligent monitoring platform based on big data proposed in this paper is 2.142 seconds, the transaction passing rate is 100%, and the platform performance test can pass. Through this platform, online real-time monitoring and remote control can be carried out in real time to grasp the dynamic changes of the environment, so that environmental problems can be found and treated in a timely manner, the environmental protection department's ability to prevent and control environmental pollution can be effectively improved, and it can also provide future urban pollution monitoring research.

Confidentiality is an indispensable requirement in financial applications of blockchain technology, and supporting it along with high performance and friendly programmability is technically challenging. In this paper, we present a system design called CONFIDE to support on-chain confidentiality by leveraging Trust Execution Environment (TEE). CONFIDE's secure data transmission protocol and data encryption protocol, together with a highly efficient virtual machine run in TEE, guarantee the confidentiality in the life cycle of a transaction from end to end. CONFIDE proposes a secure data model along with an application-driven secure protocol to guarantee data confidentiality and integrity. Its smart contract language extension offers users the flexibility to define complex confidentiality models. CONFIDE is implemented as a plugin module to Antfin Blockchain's proprietary platform, and can be plugged into other blockchain platforms as well with its universal interface design. Nowadays, CONFIDE is supporting millions of commercial transactions daily on consortium blockchain running financial applications including supply chain finance, ABS, commodity provenance, and cold-chain logistics.

Massive MIMO technique is expected to greatly improve spectrum efficiency as well as energy efficiency of a communication system. However, to obtain the benefits, the system needs to get the ideal channel state information (CSI). In practice, however, a pilot-based channel estimation scheme needs to be applied to obtain the CSI, which may cause a serious pilot contamination problem for multi-cell massive MIMO systems. To deal with this issue, an Iterative Interference Cancellation based MMSE Channel Estimation Algorithm is proposed in this paper, by iteratively eliminating the inter-cell interference. Compared to conventional channel estimation algorithms, the proposed algorithm can effectively improve the channel estimation accuracy of a target cell with low computational complexity. Simulation results are provided to demonstrate the advantage of the proposed algorithm.

In this paper we devise a holistic solution to the pursuer-evader tracking problem taking into account the limitations of the wireless sensor networks (WSNs) as well as the dynamics of both the pursuer and evader. More specifically, we present an optimal strategy for the pursuer to capture the evader despite the delayed and imprecise information available at the pursuer-side. In order to minimize the communication overhead while ensuring capture, we provide an optimal evader sampling scheme that adjusts the sampling frequency based on the strategies of the pursuer and evader, as well as the distance between the pursuer and evader. We support our adaptive sampling scheme with a just-in-time delivery protocol that publishes the evader's location updates directly to the pursuer, reducing the communication overhead of tracking even further. To further enhance the tracking reliability, we use a two-level design of fault tolerance: 1) a double position advertisement scheme to mask single message losses, and 2) a breadcrumbs-based backup scheme for stabilizing from desynchronization.Our simulation results show that the adaptive sampling scheme guides the pursuer to capture the evader effectively, and reduces the communication overhead significantly compared to fixed rate sampling. Our simulation results also show that our two-level fault-tolerance strategy ensures high capture rates even under consecutive message losses.

In contrast to traditional wireless sensor network (WSN) applications that perform only data collection and aggregation, the new generation of information processing applications such as pursuit-evasion games, tracking, evacuation, and disaster relief applications require in-network information storage and querying. Due to the resource limitations of WSNs, it is challenging to implement in-network querying in a distributed, lightweight, resilient, and energy-efficient manner. We address these challenges by exploiting location information and the geometry of the network and propose an in-network querying framework, namely, the Distributed Quad-Tree (DQT). DQT is distance sensitive for querying of an event: the cost of answering a query for an event is at most a constant factor (2radic(2) in our case) of the distance *d* to the event. DQT construction is local and does not require any communication. Moreover, due to its minimalist infrastructure and stateless nature, DQT shows graceful resilience to node failures and topology changes. Since event-based querying is inherently limited to the anticipated types of inquiries, we further extend our framework to achieve complex range-based querying. To this end, we use a multiresolution algorithm, which is optimal with respect to least square errors that models the data in a decentralized way. Our model-based scheme answers queries with approximate values accompanied by certainty levels with increased resolution at lower layers of the DQT hierarchy. Our analysis and experiments show that our framework achieves distance sensitivity and resiliency for event-based querying, as well as greatly reduces the cost of complex range querying.

In a mobile ad hoc network, tracking protocols need to deal with-in addition to the mobility of the target- the mobility of the intermediate nodes that maintain a track toward the target. To address this problem, we propose the MDQT (Mobility-enhanced Distributed QuadTree) tracking framework. MDQT employs a static cell abstraction to mask the mobility of the nodes and provide the illusion of a logical static network overlaid on the mobile network. MDQT implements this virtual static network layer in a lightweight/communication-free manner by exploiting the soft-state principle and the snooping feature of wireless communication. Using simulations, we study the effects of the mobility speed and the percentage of mobile nodes on the performance of our MDQT framework. We find that even at very high mobility speeds (50 meters per second), low update rates (1 update per second), and 100% node mobility, the success rate of MDQT tracking is above 85% and the latency is comparable with that of static networks.

In contrast to the traditional wireless sensor network (WSN) applications that perform only data collection and aggregation, new generation of information processing applications, such as pursuit-evasion games, tracking, evacuation, and disaster relief applications, require in-network information storage and querying. Due to the resource limitations of WSNs, it is challenging to implement in-network information storage and querying in a resilient, energy-efficient, and distributed manner. To address these challenges, we exploit location information and geometry of the network and present an in-network querying infrastructure, namely distributed quad-tree (DQT) structure. DQT satisfies efficient in-network information storage as well as distance-sensitive querying: the cost of answering a query for an event is at most a constant factor (in our case 2radic2 ) of the distance "d" to the nearest event in the network. DQT construction is local and does not require any communication. Moreover, due to its minimalist infrastructure and stateless nature, DQT shows graceful resilience to the face of failures.

In mobile ad hoc networks(MANET), the limited wireless spectrum, distributed multiple access control, low complexity, and high mobility together impose significant challenges for MAC protocol design to provide reliable wireless communications with high data rates. In contention based MAC protocols, such as 802.11 MAC, each multi-hop data flow encounters contentions not only from the transmissions of itself, but also from other flows that bypassing the neighborhood. This paper presents a Dynamic Token Ring based MAC protocol(DRP) for mobile ad hoc networks, which aims to solve the intra-flow and inter-flow contention problems in MAC layer. It is called dynamic, since the token ring in a cluster can be a low-priority ring or a high priority ring. The node can join high priority ring dynamically according to transmission status. Our simulation results show that DRP protocol has superior performance in improving data delivery efficiency and avoiding collisions. It is a good solution for inter-flow/intra-flow contention problems as well as hidden/exposed terminal problems.

Future wireless networks will see a combination of 3G WWANs and WLANs, which provide data services at different rates and with different coverages. New handoff management schemes are required in such heterogeneous networks to ensure the continuation of application sessions with low handoff cost. This paper proposes a novel service-oriented vertical handoff scheme between 802.11b (WLAN) and cdma2000 (3G cellular), which reduces unnecessary handoffs while providing quality-of-service (QoS) support for applications. Different handoff processes will be performed for different service types according to QoS requirements. The analytical and simulation results both show that the proposed scheme greatly improves handoff efficiency, provides a better handoff trigger, and reduces network overhead with low handoff latency.