Abstract: One or more devices may receive attribute information identifying multiple attributes associated with a client device; classify the client device based on the attribute information; and provide, based on classifying the client device, classification information to a network device to cause the network device to associate a particular policy set, of multiple policy sets, with the client device. The classification information may identify a classification of the client device. The particular policy set may be based on the classification of the client device and may include an instruction used to process a data flow provided to or provided from the client device.

Abstract: Exemplary machine-to-machine (“M2M”) device client systems, methods, and interfaces are described herein. An exemplary M2M device includes an M2M device client configured to provide 1) a platform messaging interface through which the M2M device client communicates with an M2M platform and 2) an application interface that includes a set of application program interfaces (“APIs”) through which an application installed on the M2M device interfaces with the M2M device client. The set of APIs may include one or more of the exemplary APIs and/or API function calls described herein. Corresponding systems, methods, and interfaces are also described.

Abstract: An exemplary method includes a machine-to-machine (“M2M”) rules management system associated with an M2M platform 1) processing a plurality of events associated with one or more M2M objects in substantially real-time as the events occur over a period of time, 2) receiving, while the events are being processed in substantially real-time, data representative of a rule created by a user associated with the M2M platform, and 3) dynamically applying, in response to receiving the data representative of the rule, the rule to the substantially real-time processing of the events. Corresponding methods and systems are also disclosed.

Abstract: Exemplary machine-to-machine (“M2M”) systems and methods are disclosed herein. An exemplary method includes an M2M platform system operating an M2M platform in accordance with a functionality set of the M2M platform, receiving data representative of an update to the functionality set of the M2M platform, and seamlessly transitioning, based on the data representative of the update and during runtime operation of the M2M platform, from the operating of the M2M platform in accordance with the functionality set of the M2M platform to operating the M2M platform in accordance with an updated functionality set of the M2M platform. Corresponding systems and methods are also disclosed.

Abstract: One or more devices may receive attribute information identifying multiple attributes associated with a client device; classify the client device based on the attribute information; and provide, based on classifying the client device, classification information to a network device to cause the network device to associate a particular policy set, of multiple policy sets, with the client device. The classification information may identify a classification of the client device. The particular policy set may be based on the classification of the client device and may include an instruction used to process a data flow provided to or provided from the client device.

Abstract: Exemplary machine-to-machine (“M2M”) device client systems, methods, and interfaces are described herein. An exemplary M2M device includes an M2M device client configured to provide 1) a platform messaging interface through which the M2M device client communicates with an M2M platform and 2) an application interface that includes a set of application program interfaces (“APIs”) through which an application installed on the M2M device interfaces with the M2M device client. The set of APIs may include one or more of the exemplary APIs and/or API function calls described herein. Corresponding systems, methods, and interfaces are also described.

Abstract: Exemplary machine-to-machine (“M2M”) systems and methods are disclosed herein. An exemplary method includes an M2M platform system operating an M2M platform in accordance with a functionality set of the M2M platform, receiving data representative of an update to the functionality set of the M2M platform, and seamlessly transitioning, based on the data representative of the update and during runtime operation of the M2M platform, from the operating of the M2M platform in accordance with the functionality set of the M2M platform to operating the M2M platform in accordance with an updated functionality set of the M2M platform. Corresponding systems and methods are also disclosed.

Abstract: The present disclosure is directed to generating REIT-based pure property return indexes. First, REIT return data is compiled from each REIT of a plurality of REITs at a predetermined frequency. Then, the generated REIT return data is de-levered and processed according to exposures to each of a plurality of target characteristics to obtain coefficients reflecting each REIT's weight in an index. Finally, an index is generated according to the REITs, the obtained coefficients, and the weights.

Abstract: Methods and apparatus for machine-to-machine communications are disclosed. A communications server provides a way for application servers on the Internet to communicate with a plurality of physically remote devices that do not have “traditional” Internet connections. Communications between an application server and its remote devices are normalized by the communications server so that the need for a variety of wired and wireless protocols remains transparent to the application server. In addition, the application server may initiate communications with remote devices using dynamic IP addresses, because the communications server discovers dynamic IP addresses using a non-IP based protocol.

Abstract: The present disclosure is directed to a method of approximating prices in a private property market. First, REIT return data is compiled from each REIT of a plurality of REITs at a predetermined frequency. Then, the REIT return data is processed according to exposures to each of a plurality of target characteristics to obtain coefficients reflecting each REIT's weight in an index. Then, an index is generated according to the REITs, the obtained coefficients, and the weights. Finally, a second index is derived from the generated index that approximates prices in the private property market.

Abstract: The present disclosure is directed to a method of approximating prices in a private property market. First, REIT return data is compiled from each REIT of a plurality of REITs at a predetermined frequency. Then, the REIT return data is processed according to exposures to each of a plurality of target characteristics to obtain coefficients reflecting each REIT's weight in an index. Then, an index is generated according to the REITs, the obtained coefficients, and the weights. Finally, a second index is derived from the generated index that approximates prices in the private property market.

Abstract: The present disclosure is directed to generating REIT-based pure property return indexes. First, REIT return data is compiled from each REIT of a plurality of REITs at a predetermined frequency. Then, the generated REIT return data is de-levered and processed according to exposures to each of a plurality of target characteristics to obtain coefficients reflecting each REIT's weight in an index. Finally, an index is generated according to the REITs, the obtained coefficients, and the weights.

Abstract: Indexes of commercial property prices face much scarcer transactions data than housing indexes, yet the advent of tradable derivatives on commercial property places a premium on both high frequency and accuracy of such indexes. The dilemma is that with scarce data a low-frequency return index (such as annual) is necessary to accumulate enough sales data in each period. This invention presents an approach to address this problem using a two-stage procedure with frequency conversion, by first estimating lower-frequency indexes staggered in time, and then applying a generalized inverse estimator to convert from lower to higher frequency return series. The two-stage procedure can improve the accuracy of high-frequency indexes in scarce data environments, and also can mitigate an errors-in-variables problem that arises at very high frequency even with plentiful data (e.g., monthly indexes).

Abstract: Method for establishing a commercial real estate price change index supporting tradable derivatives. The method utilizes a database of price changes actually experienced by individual commercial properties including allowing for gradual accumulation of price data. The database is filtered with selected data filters and time-weighted dummy variables are specified. A repeat-sales regression is performed on the filtered database to create the index. The repeat-sales regression includes a weighted least squares estimation in which weights are determined in a three-stage regression process. A ridge regression noise filter in which a first order autocorrelation coefficient in estimated index price-change returns controls the ridge estimation, and the first autocorrelation coefficient is near 0. The index is optimized for derivative trading purposes by excluding backward adjustments and a scope and frequency for the index is selected. The index may be used for tradable derivatives.

Abstract: Methods and apparatus for machine-to-machine communications are disclosed. A communications server provides a way for application servers on the Internet to communicate with a plurality of physically remote devices that do not have “traditional” Internet connections. Communications between an application server and its remote devices are normalized by the communications server so that the need for a variety of wired and wireless protocols remains transparent to the application server. In addition, the application server may initiate communications with remote devices using dynamic IP addresses, because the communications server discovers dynamic IP addresses using a non-IP based protocol.